diff --git a/.gitignore b/.gitignore index 8a3f423..8961a01 100644 --- a/.gitignore +++ b/.gitignore @@ -66,3 +66,4 @@ nli-data/* nlidata/* rel_ext_data* *_solved.ipynb +.DS_Store diff --git a/README.md b/README.md index c813a82..4e8b300 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ Code for [the Stanford course](http://web.stanford.edu/class/cs224u/). -Fall 2020 +Spring 2021 # Instructors @@ -35,9 +35,9 @@ A generic optimization class (`torch_model_base.py`) and subclasses for GloVe, A Reference implementations for the `torch_*.py` models, designed to reveal more about how the optimization process works. -## `vsm_*` and `hw_wordsim.ipynb` +## `vsm_*` and `hw_wordrelatedness.ipynb` -A until on vector space models of meaning, covering traditional methods like PMI and LSA as well as newer methods like Autoencoders and GloVe. `vsm.py` provides a lot of the core functionality, and `torch_glove.py` and `torch_autoencoder.py` are the learned models that we cover. `vsm_03_retroffiting.ipynb` is an extension that uses `retrofitting.py`. +A until on vector space models of meaning, covering traditional methods like PMI and LSA as well as newer methods like Autoencoders and GloVe. `vsm.py` provides a lot of the core functionality, and `torch_glove.py` and `torch_autoencoder.py` are the learned models that we cover. `vsm_03_retroffiting.ipynb` is an extension that uses `retrofitting.py`, and `vsm_04_contextualreps.ipynb` explores methods for deriving static representations from contextual models. ## `sst_*` and `hw_sst.ipynb` @@ -60,9 +60,9 @@ A unit on Natural Language Inference. `nli.py` provides core interfaces to a var A unit on grounded natural language generation, focused on generating context-dependent color descriptions using the [English Stanford Colors in Context dataset](https://cocolab.stanford.edu/datasets/colors.html). -## `contextualreps.ipynb` +## `finetuning.ipynb` -Using pretrained parameters from [Hugging Face](https://huggingface.co) and [AllenNLP](https://allennlp.org) for featurization and fine-tuning. +Using pretrained parameters from [Hugging Face](https://huggingface.co) for featurization and fine-tuning. ## `evaluation_*.ipynb` and `projects.md` diff --git a/colors.py b/colors.py index 02a0787..4c8d6e2 100644 --- a/colors.py +++ b/colors.py @@ -5,7 +5,7 @@ import matplotlib.patches as mpatch __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" TURN_BOUNDARY = " ### " diff --git a/colors_overview.ipynb b/colors_overview.ipynb index 0d7620c..e2f4f86 100644 --- a/colors_overview.ipynb +++ b/colors_overview.ipynb @@ -9,12 +9,12 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -257,7 +257,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABECAYAAADHnXQVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAABLUlEQVR4nO3YMUrEUBRA0XyZSiutnC24EjvXajcrcQtOpZW2315kVMgQ5nJOmxTvweURMuacC5RcbT0ArE3U5IiaHFGTI2pydqcejjEu/tfInHP85b3nu/eL33VZluXp7fbXfR9uPhO7vnxc/7irS02OqMkRNTknv6m/u398Pdccqzke9luPwMZcanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9Tk7P7z8vGwP9ccsBqXmhxRkyNqcsacc+sZYFUuNTmiJkfU5IiaHFGTI2pyvgBwhhdAIEFGnQAAAABJRU5ErkJggg==\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -295,7 +295,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABECAYAAADHnXQVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAABFUlEQVR4nO3YsW1CMRRAUX+UCipShRXYhCqzpsomrJBUSRVaswAiFEiIq3Nau3hPunLhZc45oGT16AHg3kRNjqjJETU5oibn5drhfnN6+q+R4996ueXe7vD99LuOMcbX59u/+368/iZ2ff/ZXtzVS02OqMkRNTmiJkfU5IiaHFGTI2pyRE2OqMkRNTmiJkfU5IiaHFGTI2pyRE2OqMkRNTmiJkfU5IiaHFGTI2pyRE2OqMkRNTmiJkfU5IiaHFGTI2pyRE2OqMkRNTmiJkfU5IiaHFGTI2pyRE2OqMkRNTmiJkfU5IiaHFGTI2pyRE2OqMkRNTmiJkfU5IianGXO+egZ4K681OSImhxRkyNqckRNjqjJOQNHYRKDRd/3AwAAAABJRU5ErkJggg==\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -338,7 +338,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -580,7 +580,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -619,7 +619,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -658,7 +658,7 @@ }, { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAALUAAABECAYAAADHnXQVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAABK0lEQVR4nO3YwUnEUBRA0XyZCnRlH4rDtGC9tiAO2ocrbeHbgIxZBMJcz9kmi/fg8ggZc84FSm72HgC2JmpyRE2OqMkRNTmHSw+/7z6v/tfI7df9WPPey+PH1e+6LMvy/P7w575jjMSuc85fd3WpyRE1OaIm5+I3Nf/D29Pr3iOscjyfVr3nUpMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaImR9TkiJocUZMjanJETY6oyRE1OaIm57D3AOzveD7tPcKmXGpyRE2OqMkZc869Z4BNudTkiJocUZMjanJETY6oyfkBPhUWwkgMDc4AAAAASUVORK5CYII=\n", + "image/png": "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\n", "text/plain": [ "
" ] @@ -945,7 +945,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 200 of 200; error is 0.26593604683876043" + "Finished epoch 200 of 200; error is 0.26593607664108276" ] } ], @@ -1106,7 +1106,9 @@ } ], "source": [ - "toy_mod.corpus_bleu(toy_color_seqs_test, toy_word_seqs_test)" + "bleu_score, predicted_texts = toy_mod.corpus_bleu(toy_color_seqs_test, toy_word_seqs_test)\n", + "\n", + "bleu_score" ] }, { @@ -1216,8 +1218,8 @@ "output_type": "stream", "text": [ "{'': 1.0, '': 0.0, 'A': 0.0, 'B': 0.0, '$UNK': 0.0}\n", - "{'': 0.00018379976, '': 0.00022975517, 'A': 0.9946944, 'B': 0.004481194, '$UNK': 0.00041091075}\n", - "{'': 0.0010102483, '': 0.023374218, 'A': 0.0016727167, 'B': 0.9730926, '$UNK': 0.0008501807}\n", + "{'': 0.00018379976, '': 0.00022975517, 'A': 0.9946944, 'B': 0.004481194, '$UNK': 0.00041091096}\n", + "{'': 0.0010102493, '': 0.02337423, 'A': 0.0016727175, 'B': 0.9730926, '$UNK': 0.00085018104}\n", "{'': 0.0046478347, '': 0.9801214, 'A': 0.01115099, 'B': 0.0027307996, '$UNK': 0.001349019}\n" ] } @@ -1250,7 +1252,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 200 of 200; error is 0.42917731404304504" + "/Applications/anaconda3/envs/nlu/lib/python3.8/site-packages/numpy/core/_asarray.py:83: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray\n", + " return array(a, dtype, copy=False, order=order)\n", + "Finished epoch 200 of 200; error is 0.45002618432044983" ] }, { @@ -1427,15 +1431,15 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 12. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 60.62587070465088" + "Stopping after epoch 17. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 57.85624027252197" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 4min 17s, sys: 8.47 s, total: 4min 26s\n", - "Wall time: 1min 6s\n" + "CPU times: user 1min 50s, sys: 5.29 s, total: 1min 55s\n", + "Wall time: 56.9 s\n" ] } ], @@ -1454,28 +1458,49 @@ "cell_type": "code", "execution_count": 52, "metadata": {}, + "outputs": [], + "source": [ + "dev_mod_eval = dev_mod.evaluate(dev_cols_test, dev_word_seqs_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/cgpotts/Documents/teaching/2019-2020/xcs224u/cs224u/torch_color_describer.py:678: RuntimeWarning: divide by zero encountered in power\n", - " perp = [np.prod(s)**(-1/len(s)) for s in scores]\n" - ] - }, + "data": { + "text/plain": [ + "0.367117765620501" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dev_mod_eval['listener_accuracy']" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ { "data": { "text/plain": [ - "{'listener_accuracy': 0.32450331125827814, 'corpus_bleu': 0.05031672905269219}" + "0.05830693924560899" ] }, - "execution_count": 52, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "dev_mod.evaluate(dev_cols_test, dev_word_seqs_test)" + "dev_mod_eval['corpus_bleu']" ] }, { @@ -1517,7 +1542,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 55, "metadata": {}, "outputs": [], "source": [ @@ -1542,7 +1567,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 56, "metadata": {}, "outputs": [], "source": [ @@ -1567,7 +1592,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 57, "metadata": {}, "outputs": [], "source": [ @@ -1601,7 +1626,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 58, "metadata": {}, "outputs": [], "source": [ @@ -1613,14 +1638,14 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 59, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 0.10807410627603531" + "Finished epoch 1000 of 1000; error is 0.12768782675266266" ] } ], @@ -1630,7 +1655,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 60, "metadata": {}, "outputs": [ { @@ -1639,7 +1664,7 @@ "1.0" ] }, - "execution_count": 58, + "execution_count": 60, "metadata": {}, "output_type": "execute_result" } @@ -1673,7 +1698,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 61, "metadata": {}, "outputs": [], "source": [ @@ -1711,7 +1736,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 62, "metadata": {}, "outputs": [], "source": [ @@ -1747,7 +1772,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 63, "metadata": {}, "outputs": [], "source": [ @@ -1759,14 +1784,14 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 64, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 0.13370060920715332" + "Finished epoch 1000 of 1000; error is 0.1362161487340927" ] } ], @@ -1776,22 +1801,22 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'listener_accuracy': 1.0, 'corpus_bleu': 1.0}" + "1.0" ] }, - "execution_count": 63, + "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "mod_deep.evaluate(toy_color_seqs_test, toy_word_seqs_test)" + "mod_deep.listener_accuracy(toy_color_seqs_test, toy_word_seqs_test)" ] } ], @@ -1811,9 +1836,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/contextualreps.ipynb b/contextualreps.ipynb deleted file mode 100644 index 41565a2..0000000 --- a/contextualreps.ipynb +++ /dev/null @@ -1,1576 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Bringing contextual word representations into your models" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Contents\n", - "\n", - "1. [Overview](#Overview)\n", - "1. [General set-up](#General-set-up)\n", - "1. [Hugging Face BERT interfaces](#Hugging-Face-BERT-interfaces)\n", - " 1. [Hugging Face BERT set-up](#Hugging-Face-BERT-set-up)\n", - " 1. [Hugging Face BERT basics](#Hugging-Face-BERT-basics)\n", - " 1. [BERT featurization with Hugging Face](#BERT-featurization-with-Hugging-Face)\n", - " 1. [Simple feed-forward experiment](#Simple-feed-forward-experiment)\n", - " 1. [A feed-forward experiment with the sst module](#A-feed-forward-experiment-with-the-sst-module)\n", - " 1. [An RNN experiment with the sst module](#An-RNN-experiment-with-the-sst-module)\n", - " 1. [BERT fine-tuning with Hugging Face](#BERT-fine-tuning-with-Hugging-Face)\n", - " 1. [HfBertClassifier](#HfBertClassifier)\n", - " 1. [HfBertClassifier experiment](#HfBertClassifier-experiment)\n", - "1. [Using ELMo](#Using-ELMo)\n", - " 1. [ELMo Allen NLP set-up](#ELMo-Allen-NLP-set-up)\n", - " 1. [ELMo fine-tuning](#ELMo-fine-tuning)\n", - " 1. [AllenNLP ELMo interfaces](#AllenNLP-ELMo-interfaces)\n", - " 1. [ElmoRNNClassifier](#ElmoRNNClassifier)\n", - " 1. [ElmoRNNClassifier experiment](#ElmoRNNClassifier-experiment)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Overview\n", - "\n", - "This notebook provides a basic introduction to using pre-trained [BERT](https://github.com/google-research/bert) and [ELMo](https://allennlp.org/elmo) representations. It is meant as a practical companion to our lecture on contextual word representations. The goal of this notebook is just to help you use these representations in your own work. The BERT and ELMo teams have done amazing work to make these resources available to the community. Many projects can benefit from them, so it is probably worth your time to experiment.\n", - "\n", - "This notebook should be considered an experimental extension to the regular course materials. It has some special requirements – libraries and data files – that are not part of the core requirements for this repository. All these tools are very new and being updated frequently, so you might need to do some fiddling to get all of this to work. As I said, though, it's probably worth the effort!\n", - "\n", - "A number of the experiments in this notebook are resource intensive. I've included timing information for the expensive steps, to give you a sense for how long things are likely to take. I ran this notebook on a laptop with a single NVIDIA RTX 2080 GPU. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## General set-up\n", - "\n", - "The following are requirements that you'll already have met if you've been working in this repository. As you can see, we'll use the [Stanford Sentiment Treebank](sst_01_overview.ipynb) for illustrations, and we'll try out a few different deep learning models." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import sst\n", - "from torch_shallow_neural_classifier import TorchShallowNeuralClassifier\n", - "from torch_rnn_classifier import TorchRNNModel\n", - "from torch_rnn_classifier import TorchRNNClassifier\n", - "from torch_rnn_classifier import TorchRNNClassifierModel\n", - "from torch_rnn_classifier import TorchRNNClassifier\n", - "from sklearn.metrics import classification_report\n", - "import utils" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "utils.fix_random_seeds()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "SST_HOME = os.path.join(\"data\", \"trees\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Hugging Face BERT interfaces" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Hugging Face BERT set-up\n", - "\n", - "To install this library, run\n", - "\n", - "```pip install transformers```\n", - "\n", - "I've tested this code with versions 2.4, 2.5, and 2.11 of `transformers`. Try to get at least 2.5. It requires `pip >= 20` and, I think, a version of [Rust](https://www.rust-lang.org) at least as high as 1.21.1." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import torch\n", - "import torch.nn as nn\n", - "from transformers import BertModel, BertTokenizer" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `transformers` library does a lot of logging. To avoid ending up with a cluttered notebook, I am changing the logging level. You might want to skip this as you scale up to building production systems, since the logging is very good – it gives you a lot of insights into what the models and code are doing." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "import logging\n", - "logger = logging.getLogger()\n", - "logger.level = logging.ERROR" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Hugging Face BERT basics\n", - "\n", - "To start, let's get a feel for the basic API that `transformers` provides. The first step is specifying the pretrained parameters we'll be using:" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "hf_weights_name = 'bert-base-cased'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "There are lots other options for pretrained weights. See [this section of the project README.md](https://github.com/huggingface/transformers#quick-tour) for a good overview and code that documents how these weights align with different Transformer model classes." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Next, we specify a tokenizer and a model that match both each other and our choice of pretrained weights:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "hf_tokenizer = BertTokenizer.from_pretrained(hf_weights_name)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "3cc30d02a7d94499a5db796f860340c0" - } - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "hf_model = BertModel.from_pretrained(hf_weights_name)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "It's illuminating to see what the tokenizer does to example texts:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "hf_example_texts = [\n", - " \"Encode sentence 1. [SEP] And sentence 2!\",\n", - " \"Bert knows Snuffleupagus\"]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `encode` method maps individual strings to indices into the underlying embedding used by the model:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[101, 13832, 13775, 5650, 122, 119, 102, 1262, 5650, 123, 106, 102]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ex0_ids = hf_tokenizer.encode(hf_example_texts[0], add_special_tokens=True)\n", - "\n", - "ex0_ids" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can get a better feel for what these representations are like by mapping the indices back to \"words\":" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['[CLS]',\n", - " 'En',\n", - " '##code',\n", - " 'sentence',\n", - " '1',\n", - " '.',\n", - " '[SEP]',\n", - " 'And',\n", - " 'sentence',\n", - " '2',\n", - " '!',\n", - " '[SEP]']" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "hf_tokenizer.convert_ids_to_tokens(ex0_ids)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For modeling, we will often need to pad (and perhaps truncate) token lists so that we can work with fixed-dimensional tensors: The `batch_encode_plus` has a lot of options for doing this:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "hf_example_ids = hf_tokenizer.batch_encode_plus(\n", - " hf_example_texts,\n", - " add_special_tokens=True,\n", - " return_attention_mask=True,\n", - " pad_to_max_length=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "dict_keys(['input_ids', 'token_type_ids', 'attention_mask'])" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "hf_example_ids.keys()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `token_type_ids` is used for multi-text inputs like NLI. The `'input_ids'` field gives the indices for each of the two examples:" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[[101, 13832, 13775, 5650, 122, 119, 102, 1262, 5650, 123, 106, 102],\n", - " [101, 15035, 3520, 156, 14787, 13327, 4455, 28026, 1116, 102, 0, 0]]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "hf_example_ids['input_ids']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For fine-tuning, we want to avoid attending to padded tokens. The `'attention_mask'` captures the needed mask, which we'll be able to feed directly to the pretrained BERT model:" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0]]" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "hf_example_ids['attention_mask']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally, we can run these indices and masks through the pretrained model:" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "X_hf_example = torch.tensor(hf_example_ids['input_ids'])\n", - "X_hf_example_mask = torch.tensor(hf_example_ids['attention_mask'])\n", - "\n", - "with torch.no_grad():\n", - " hf_final_hidden_states, cls_output = hf_model(\n", - " X_hf_example, attention_mask=X_hf_example_mask)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "BERT representations are pretty large – this shows the shape of the tensor for 2 examples, with the second padded to the length of the larger one in the batch (12). The individual representations have dimensionality 768." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "torch.Size([2, 12, 768])" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "hf_final_hidden_states.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Those are all the essential ingredients for working with these parameters in Hugging Face. Of course, the library has a lot of other functionality, but the above suffices to featurize and to fine-tune." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### BERT featurization with Hugging Face\n", - "\n", - "To start, we'll use the Hugging Face interfaces just to featurize examples to create inputs to a separate model. In this setting, the BERT parameters are frozen. The heart of this approach is the following featurizer, which flattens an SST tree into a string, tokenizes it, and computes its hidden representations:" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "def hugging_face_bert_phi(tree):\n", - " s = \" \".join(tree.leaves())\n", - " input_ids = hf_tokenizer.encode(s, add_special_tokens=True)\n", - " X = torch.tensor([input_ids])\n", - " with torch.no_grad():\n", - " final_hidden_states, cls_output = hf_model(X)\n", - " return final_hidden_states.squeeze(0).numpy()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Simple feed-forward experiment\n", - "\n", - "For a simple feed-forward experiment, we can get the representation of the `[CLS]` tokens and use them as the inputs to a shallow neural network:" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [], - "source": [ - "def hugging_face_bert_classifier_phi(tree):\n", - " reps = hugging_face_bert_phi(tree)\n", - " #return reps.mean(axis=0) # Another good, easy option.\n", - " return reps[0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Next we read in the SST train and dev portions as a lists of `(tree, label)` pairs:" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "hf_train = list(sst.train_reader(SST_HOME, class_func=sst.binary_class_func))\n", - "\n", - "hf_dev = list(sst.dev_reader(SST_HOME, class_func=sst.binary_class_func))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Split the input/output pairs out into separate lists:" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [], - "source": [ - "X_hf_tree_train, y_hf_train = zip(*hf_train)\n", - "\n", - "X_hf_tree_dev, y_hf_dev = zip(*hf_dev)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In the next step, we featurize all of the examples. These steps are likely to be the slowest in these experiments:" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 34min 55s, sys: 6.99 s, total: 35min 2s\n", - "Wall time: 5min 52s\n" - ] - } - ], - "source": [ - "%time X_hf_train = [hugging_face_bert_classifier_phi(tree)\n", - " for tree in X_hf_tree_train]" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 4min 13s, sys: 868 ms, total: 4min 13s\n", - "Wall time: 42.6 s\n" - ] - } - ], - "source": [ - "%time X_hf_dev = [hugging_face_bert_classifier_phi(tree)\n", - " for tree in X_hf_tree_dev]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now that all the examples are featurized, we can fit a model and evaluate it:" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], - "source": [ - "hf_mod = TorchShallowNeuralClassifier(\n", - " early_stopping=True,\n", - " hidden_dim=300)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 38. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 2.0183719843626022" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 19.2 s, sys: 496 ms, total: 19.7 s\n", - "Wall time: 5.28 s\n" - ] - } - ], - "source": [ - "%time _ = hf_mod.fit(X_hf_train, y_hf_train)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": {}, - "outputs": [], - "source": [ - "hf_preds = hf_mod.predict(X_hf_dev)" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " precision recall f1-score support\n", - "\n", - " negative 0.850 0.834 0.842 428\n", - " positive 0.843 0.858 0.850 444\n", - "\n", - " accuracy 0.846 872\n", - " macro avg 0.846 0.846 0.846 872\n", - "weighted avg 0.846 0.846 0.846 872\n", - "\n" - ] - } - ], - "source": [ - "print(classification_report(y_hf_dev, hf_preds, digits=3))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### A feed-forward experiment with the sst module\n", - "\n", - "It is straightforward to conduct experiments like the above using `sst.experiment`, which will enable you to do a wider range of experiments without writing or copy-pasting a lot of code. " - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_hf_shallow_network(X, y):\n", - " mod = TorchShallowNeuralClassifier(\n", - " hidden_dim=300,\n", - " early_stopping=True)\n", - " mod.fit(X, y)\n", - " return mod" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 22. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 2.3845930993556976" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " precision recall f1-score support\n", - "\n", - " negative 0.839 0.839 0.839 428\n", - " positive 0.845 0.845 0.845 444\n", - "\n", - " accuracy 0.842 872\n", - " macro avg 0.842 0.842 0.842 872\n", - "weighted avg 0.842 0.842 0.842 872\n", - "\n", - "CPU times: user 42min 27s, sys: 8.83 s, total: 42min 36s\n", - "Wall time: 7min 8s\n" - ] - } - ], - "source": [ - "%%time\n", - "_ = sst.experiment(\n", - " SST_HOME,\n", - " hugging_face_bert_classifier_phi,\n", - " fit_hf_shallow_network,\n", - " train_reader=sst.train_reader,\n", - " assess_reader=sst.dev_reader,\n", - " class_func=sst.binary_class_func,\n", - " vectorize=False) # Pass in the BERT reps directly!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### An RNN experiment with the sst module\n", - "\n", - "We can also use BERT representations as the input to an RNN. There is just one key change from how we used these models before:\n", - "\n", - "* Previously, we would feed in lists of tokens, and they would be converted to indices into a fixed embedding space. This presumes that all words have the same representation no matter what their context is. \n", - "\n", - "* With BERT, we skip the embedding entirely and just feed in lists of BERT vectors, which means that the same word can be represented in different ways.\n", - "\n", - "`TorchRNNClassifier` supports this via `use_embedding=False`. In turn, you needn't supply a vocabulary:" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_hf_rnn(X, y):\n", - " mod = TorchRNNClassifier(\n", - " vocab=[],\n", - " early_stopping=True,\n", - " use_embedding=False) # Pass in the BERT hidden states directly!\n", - " mod.fit(X, y)\n", - " return mod" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 25. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.9420086964964867" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " precision recall f1-score support\n", - "\n", - " negative 0.849 0.853 0.851 428\n", - " positive 0.857 0.854 0.856 444\n", - "\n", - " accuracy 0.853 872\n", - " macro avg 0.853 0.853 0.853 872\n", - "weighted avg 0.853 0.853 0.853 872\n", - "\n", - "CPU times: user 44min, sys: 31.2 s, total: 44min 31s\n", - "Wall time: 7min 37s\n" - ] - } - ], - "source": [ - "%%time\n", - "_ = sst.experiment(\n", - " SST_HOME,\n", - " hugging_face_bert_phi,\n", - " fit_hf_rnn,\n", - " train_reader=sst.train_reader,\n", - " assess_reader=sst.dev_reader,\n", - " class_func=sst.binary_class_func,\n", - " vectorize=False) # Pass in the BERT hidden states directly!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### BERT fine-tuning with Hugging Face\n", - "\n", - "The above experiments are quite successful – BERT gives us a reliable boost compared to other methods we've explored for the SST task. However, we might expect to do even better if we fine-tune the BERT parameters as part of fitting our SST classifier. To do that, we need to incorporate the Hugging Face BERT model into our classifier. This too is quite straightforward." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### HfBertClassifier\n", - "\n", - "The most important step is to create an `nn.Module` subclass that has, for its parameters, both the BERT model and parameters for our own classifier. Here we define a very simple fine-tuning set-up in which some layers built on top of the output corresponding to `[CLS]` are used as the basis for the SST classifier:" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "class HfBertClassifierModel(nn.Module):\n", - " def __init__(self, n_classes, weights_name='bert-base-cased'):\n", - " super().__init__()\n", - " self.n_classes = n_classes\n", - " self.weights_name = weights_name\n", - " self.bert = BertModel.from_pretrained(self.weights_name)\n", - " self.bert.train()\n", - " self.hidden_dim = self.bert.embeddings.word_embeddings.embedding_dim\n", - " # The only new parameters -- the classifier:\n", - " self.classifier_layer = nn.Linear(\n", - " self.hidden_dim, self.n_classes)\n", - "\n", - " def forward(self, indices, mask):\n", - " final_hidden_states, cls_output = self.bert(\n", - " indices, attention_mask=mask)\n", - " return self.classifier_layer(cls_output)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As you can see, `self.bert` does the heavy-lifting: it reads in all the pretrained BERT parameters, and I've specified `self.bert.train()` just to make sure that these parameters can be updated during our training process. \n", - "\n", - "In `forward`, `self.bert` is used to process inputs, and then `cls_output` is fed into `self.classifier_layer`. Hugging Face has already added a layer on top of the actual output for `[CLS]`, so we can specify the model as\n", - "\n", - "$$\n", - "\\begin{align}\n", - "[h_{1}, \\ldots, h_{n}] &= \\text{BERT}([x_{1}, \\ldots, x_{n}]) \\\\\n", - "h &= \\tanh(h_{1}W_{hh} + b_{h}) \\\\\n", - "y &= \\textbf{softmax}(hW_{hy} + b_{y})\n", - "\\end{align}$$\n", - "\n", - "for a tokenized input sequence $[x_{1}, \\ldots, x_{n}]$. \n", - "\n", - "The Hugging Face documentation somewhat amusingly says, of `cls_output`,\n", - "\n", - "> This output is usually _not_ a good summary of the semantic content of the input, you're often better with averaging or pooling the sequence of hidden-states for the whole input sequence.\n", - "\n", - "which is entirely reasonable, but it will require more resources, so we'll do the simpler thing here." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For the training and prediction interface, we can subclass `TorchShallowNeuralClassifier` so that we don't have to write any of our own data-handling, training, or prediction code. The central changes are using `HfBertClassifierModel` in `build_graph` and processing the data with `batch_encode_plus`." - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [], - "source": [ - "class HfBertClassifier(TorchShallowNeuralClassifier):\n", - " def __init__(self, weights_name, *args, **kwargs):\n", - " self.weights_name = weights_name\n", - " self.tokenizer = BertTokenizer.from_pretrained(self.weights_name)\n", - " super().__init__(*args, **kwargs)\n", - " self.params += ['weights_name']\n", - "\n", - " def build_graph(self):\n", - " return HfBertClassifierModel(self.n_classes_, self.weights_name)\n", - "\n", - " def build_dataset(self, X, y=None):\n", - " data = self.tokenizer.batch_encode_plus(\n", - " X,\n", - " max_length=None,\n", - " add_special_tokens=True,\n", - " pad_to_max_length=True,\n", - " return_attention_mask=True)\n", - " indices = torch.tensor(data['input_ids'])\n", - " mask = torch.tensor(data['attention_mask'])\n", - " if y is None:\n", - " dataset = torch.utils.data.TensorDataset(indices, mask)\n", - " else:\n", - " self.classes_ = sorted(set(y))\n", - " self.n_classes_ = len(self.classes_)\n", - " class2index = dict(zip(self.classes_, range(self.n_classes_)))\n", - " y = [class2index[label] for label in y]\n", - " y = torch.tensor(y)\n", - " dataset = torch.utils.data.TensorDataset(indices, mask, y)\n", - " return dataset" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### HfBertClassifier experiment\n", - "\n", - "That's it! Let's see how we do on the SST binary, root-only problem. Because fine-tuning is expensive, we'll conduct a modest hyperparameter search and run the model for just one epoch per setting evaluation, as we did when [assessing NLI models](nli_02_models.ipynb)." - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [], - "source": [ - "def bert_fine_tune_phi(tree):\n", - " return \" \".join(tree.leaves())" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_hf_bert_classifier_with_hyperparameter_search(X, y):\n", - " basemod = HfBertClassifier(\n", - " weights_name='bert-base-cased',\n", - " batch_size=8, # Small batches to avoid memory overload.\n", - " max_iter=1, # We'll search based on 1 iteration for efficiency.\n", - " n_iter_no_change=5, # Early-stopping params are for the\n", - " early_stopping=True) # final evaluation.\n", - "\n", - " param_grid = {\n", - " 'gradient_accumulation_steps': [1, 4, 8],\n", - " 'eta': [0.00005, 0.0001, 0.001],\n", - " 'hidden_dim': [100, 200, 300]}\n", - "\n", - " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", - " X, y, basemod, cv=3, param_grid=param_grid)\n", - "\n", - " return bestmod" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Finished epoch 1 of 1; error is 38.469218485057354" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best params: {'eta': 5e-05, 'gradient_accumulation_steps': 8, 'hidden_dim': 300}\n", - "Best score: 0.892\n", - " precision recall f1-score support\n", - "\n", - " negative 0.953 0.808 0.875 428\n", - " positive 0.839 0.962 0.896 444\n", - "\n", - " accuracy 0.886 872\n", - " macro avg 0.896 0.885 0.885 872\n", - "weighted avg 0.895 0.886 0.886 872\n", - "\n", - "CPU times: user 1h 31min 39s, sys: 4min 6s, total: 1h 35min 46s\n", - "Wall time: 1h 36min 43s\n" - ] - } - ], - "source": [ - "%%time\n", - "hf_bert_classifier_xval = sst.experiment(\n", - " SST_HOME,\n", - " bert_fine_tune_phi,\n", - " fit_hf_bert_classifier_with_hyperparameter_search,\n", - " train_reader=sst.train_reader,\n", - " assess_reader=sst.dev_reader,\n", - " class_func=sst.binary_class_func,\n", - " vectorize=False) # Pass in the BERT hidden state directly!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And now on to the final test-set evaluation, using the best model from above:" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], - "source": [ - "optimized_hf_bert_classifier = hf_bert_classifier_xval['model']" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], - "source": [ - "# Remove the rest of the experiment results to clear out some memory:\n", - "del hf_bert_classifier_xval" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_optimized_hf_bert_classifier(X, y):\n", - " optimized_hf_bert_classifier.max_iter = 1000\n", - " optimized_hf_bert_classifier.fit(X, y)\n", - " return optimized_hf_bert_classifier" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 10. Validation score did not improve by tol=1e-05 for more than 5 epochs. Final error is 0.964973742607981" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " precision recall f1-score support\n", - "\n", - " negative 0.890 0.928 0.908 912\n", - " positive 0.924 0.884 0.904 909\n", - "\n", - " accuracy 0.906 1821\n", - " macro avg 0.907 0.906 0.906 1821\n", - "weighted avg 0.907 0.906 0.906 1821\n", - "\n", - "CPU times: user 13min 12s, sys: 17.4 s, total: 13min 29s\n", - "Wall time: 13min 29s\n" - ] - } - ], - "source": [ - "%%time\n", - "_ = sst.experiment(\n", - " SST_HOME,\n", - " bert_fine_tune_phi,\n", - " fit_optimized_hf_bert_classifier,\n", - " train_reader=(sst.train_reader, sst.dev_reader),\n", - " assess_reader=sst.test_reader,\n", - " class_func=sst.binary_class_func,\n", - " vectorize=False) # Pass in the BERT hidden state directly!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The above is just one of the many possible ways to fine-tune BERT using our course modules or new modules you write. The crux of it is creating an `nn.Module` that combines the BERT parameters with your model's new parameters." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Using ELMo" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ELMo Allen NLP set-up\n", - "\n", - "There are a number of ways to use pre-trained ELMo models. We'll use the simplest of the AllenNLP interfaces. Run the following to install [AllenNLP](https://allennlp.org):\n", - "\n", - "```sh\n", - "pip install allennlp\n", - "```\n", - "I've tested this notebook with versions, 0.8.0, 0.9.0, and 1.0.0.\n", - "\n", - "Mac users: If your installation fails, make sure your Xcode tools are up to date by running `xcode-select --install`." - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [], - "source": [ - "from allennlp.modules.elmo import Elmo, batch_to_ids\n", - "import torch\n", - "import torch.nn as nn" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We'll use the following models, which will download from S3 to a local temp directory the first time you use them with `ElmoEmbedder` or `Elmo` as described below." - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [], - "source": [ - "elmo_file_path = \"https://allennlp.s3.amazonaws.com/models/elmo/2x4096_512_2048cnn_2xhighway/\"\n", - "\n", - "options_file = elmo_file_path + \"elmo_2x4096_512_2048cnn_2xhighway_options.json\"\n", - "\n", - "weights_file = elmo_file_path + \"elmo_2x4096_512_2048cnn_2xhighway_weights.hdf5\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For more models:\n", - "\n", - "https://allennlp.org/elmo\n", - "\n", - "For additional details:\n", - "\n", - "https://docs.allennlp.org/master/api/modules/elmo/" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### ELMo fine-tuning\n", - "\n", - "Fine-tuning ELMo proceeds in essentially the same way it did for BERT: we create an `nn.Module` that combines the parameters from ELMo with our task-specific parameters and then optimize everything on the new task. To illustrate, I'll define an RNN on top of the ELMo model using new subclasses of `TorchRNNClassifier` and `TorchRNNClassifierModel`." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### AllenNLP ELMo interfaces\n", - "\n", - "To start, let's get a feel for the primary interface, and then we'll write the classes that will allow us to use these components systematically.\n", - "\n", - "The interface to the ELMo parameters in this context is the class `Elmo`:" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [], - "source": [ - "elmo = Elmo(options_file, weights_file, num_output_representations=1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This model expects tokenized inputs:" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [], - "source": [ - "elmo_example_texts = [\n", - " [\"Encode\", \"sentence\", \"1\", \".\"],\n", - " [\"ELMo\", \"knows\" \"Snuffleupagus\"]]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The ELMo model processes its tokens at the character-level, creating convolutional representations for the words from various character n-gram combinations:" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "tensor([259, 70, 111, 100, 112, 101, 102, 260, 261, 261, 261, 261, 261, 261,\n", - " 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261,\n", - " 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261, 261,\n", - " 261, 261, 261, 261, 261, 261, 261, 261])" - ] - }, - "execution_count": 52, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "elmo_character_ids = batch_to_ids(elmo_example_texts)\n", - "\n", - "# First word of the first example:\n", - "elmo_character_ids[0][0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`elmo` embeds these at the word-level:" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [], - "source": [ - "elmo_embeddings = elmo(elmo_character_ids)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`elmo_embeddings` is a dict. The value of the key `'elmo_representations'` is a list of tensors corresponding to each layer of the model. In other words, each tensor in the list is a complete representation of the example. The final element of the list is the final representation layer. I specified `num_output_representations=1` when initializing `elmo` above, so we get a list of length 1:" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[tensor([[[-0.7944, 0.0000, 0.0000, ..., -0.0000, -0.0000, -1.9283],\n", - " [-0.0000, 1.1850, 0.6947, ..., 0.0000, -0.9297, -0.2358],\n", - " [ 0.0000, 0.5358, 0.7767, ..., -0.6500, -0.0777, -0.4875],\n", - " [-0.0000, -0.4965, -0.0000, ..., -0.1605, 0.0000, 0.2256]],\n", - " \n", - " [[ 0.4553, -0.0000, 0.0000, ..., -0.0000, -0.0000, -0.5380],\n", - " [ 0.0000, -0.5309, -0.0000, ..., -0.2244, -0.0000, 0.7476],\n", - " [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000],\n", - " [ 0.0000, 0.0000, 0.0000, ..., 0.0000, 0.0000, 0.0000]]],\n", - " grad_fn=)]" - ] - }, - "execution_count": 54, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "elmo_embeddings['elmo_representations']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### ElmoRNNClassifier\n", - "\n", - "The above are the representations we will be fine-tuning. There are many ways to cdo this. In my simple illustration, I just take the top layer, as we did in the simpler featurization example above, but now keeping each word representation separate for use in the input to the task-specific RNN. Here is the `nn.Module` built on `TorchRNNClassifierModel`:" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [], - "source": [ - "class ElmoRNNClassifierModel(TorchRNNClassifierModel):\n", - " def __init__(self,\n", - " options_file,\n", - " weights_file,\n", - " rnn,\n", - " output_dim,\n", - " classifier_activation):\n", - " super().__init__(rnn, output_dim, classifier_activation)\n", - " self.options_file = options_file\n", - " self.weights_file = weights_file\n", - " self.elmo = Elmo(\n", - " self.options_file,\n", - " self.weights_file,\n", - " num_output_representations=1,\n", - " dropout=0)\n", - " self.elmo.train()\n", - "\n", - " def forward(self, X, seq_lengths):\n", - " result = self.elmo(X)\n", - " X = result['elmo_representations'][-1]\n", - " outputs, state = self.rnn(X, seq_lengths)\n", - " state = self.get_batch_final_states(state)\n", - " if self.rnn.bidirectional:\n", - " state = torch.cat((state[0], state[1]), dim=1)\n", - " h = self.classifier_activation(self.hidden_layer(state))\n", - " logits = self.classifier_layer(h)\n", - " return logits" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And here is the subclass of `TorchRNNClassifier` that lets us take advantage of all the optimization and prediction methods of that class:" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [], - "source": [ - "class ElmoRNNClassifier(TorchRNNClassifier):\n", - " def __init__(self, vocab, options_file, weights_file, **model_kwargs):\n", - " self.options_file = options_file\n", - " self.weights_file = weights_file\n", - " # Values determined by using ELMo:\n", - " model_kwargs['use_embedding'] = False\n", - " model_kwargs['embedding'] = None\n", - " model_kwargs['embed_dim'] = 1024\n", - " super().__init__(vocab, **model_kwargs)\n", - " self.params += ['options_file', 'weights_file']\n", - "\n", - " def build_graph(self):\n", - "\n", - " # The RNN is setup just as in a regular `TorchRNNClassifier`:\n", - " rnn = TorchRNNModel(\n", - " vocab_size=len(self.vocab),\n", - " embedding=self.embedding,\n", - " use_embedding=self.use_embedding,\n", - " embed_dim=self.embed_dim,\n", - " rnn_cell_class=self.rnn_cell_class,\n", - " hidden_dim=self.hidden_dim,\n", - " bidirectional=self.bidirectional,\n", - " freeze_embedding=self.freeze_embedding)\n", - "\n", - " # The Classifier layer uses our new `ElmoRNNClassifierModel`:\n", - " model = ElmoRNNClassifierModel(\n", - " options_file=self.options_file,\n", - " weights_file=self.weights_file,\n", - " rnn=rnn,\n", - " output_dim=self.n_classes_,\n", - " classifier_activation=self.classifier_activation)\n", - "\n", - " return model\n", - "\n", - " def build_dataset(self, X, y=None):\n", - " seq_lengths = [len(ex) for ex in X]\n", - " seq_lengths = torch.tensor(seq_lengths)\n", - " X = batch_to_ids(X)\n", - " if y is None:\n", - " return torch.utils.data.TensorDataset(X, seq_lengths)\n", - " else:\n", - " self.classes_ = sorted(set(y))\n", - " self.n_classes_ = len(self.classes_)\n", - " class2index = dict(zip(self.classes_, range(self.n_classes_)))\n", - " y = [class2index[label] for label in y]\n", - " y = torch.tensor(y)\n", - " return torch.utils.data.TensorDataset(X, seq_lengths, y)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### ElmoRNNClassifier experiment\n", - "\n", - "And finally here is a self-contained evaluation involving a modest hyperparameter search:" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [], - "source": [ - "def elmo_fine_tune_phi(tree):\n", - " return tree.leaves()" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_elmo_rnn_with_hyperparameter_search(X, y):\n", - " basemod = ElmoRNNClassifier(\n", - " vocab=[],\n", - " options_file=options_file,\n", - " weights_file=weights_file,\n", - " batch_size=8, # Kept small so that we can explore large networks.\n", - " max_iter=1, # We'll search based on 1 iteration for efficiency.\n", - " n_iter_no_change=5, # Early-stopping params are for the\n", - " early_stopping=True) # final evalution.\n", - "\n", - " param_grid = {\n", - " 'gradient_accumulation_steps': [1, 4, 8],\n", - " 'eta': [0.001, 0.01, 0.05],\n", - " 'hidden_dim': [50, 100, 200]}\n", - "\n", - " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", - " X, y, basemod, cv=3, param_grid=param_grid)\n", - "\n", - " return bestmod" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Finished epoch 1 of 1; error is 330.32408917695284" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best params: {'eta': 0.001, 'gradient_accumulation_steps': 1, 'hidden_dim': 200}\n", - "Best score: 0.856\n", - " precision recall f1-score support\n", - "\n", - " negative 0.848 0.848 0.848 428\n", - " positive 0.854 0.854 0.854 444\n", - "\n", - " accuracy 0.851 872\n", - " macro avg 0.851 0.851 0.851 872\n", - "weighted avg 0.851 0.851 0.851 872\n", - "\n", - "CPU times: user 2h 4min 55s, sys: 4min 16s, total: 2h 9min 12s\n", - "Wall time: 2h 1min 35s\n" - ] - } - ], - "source": [ - "%%time\n", - "elmo_rnn_xval = sst.experiment(\n", - " SST_HOME,\n", - " elmo_fine_tune_phi,\n", - " fit_elmo_rnn_with_hyperparameter_search,\n", - " train_reader=sst.train_reader,\n", - " assess_reader=sst.dev_reader,\n", - " class_func=sst.binary_class_func,\n", - " vectorize=False) # Pass in the ELMo reps directly!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And now we move to the test-set evaluation using the best model we found:" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "metadata": {}, - "outputs": [], - "source": [ - "optimized_elmo_rnn = elmo_rnn_xval['model']" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "metadata": {}, - "outputs": [], - "source": [ - "# Remove the unneeded experimental data to save memory:\n", - "del elmo_rnn_xval" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_optimized_elmo_rnn(X, y):\n", - " optimized_elmo_rnn.max_iter = 20\n", - " optimized_elmo_rnn.fit(X, y)\n", - " return optimized_elmo_rnn" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 10. Validation score did not improve by tol=1e-05 for more than 5 epochs. Final error is 27.70847176760435" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " precision recall f1-score support\n", - "\n", - " negative 0.891 0.880 0.886 912\n", - " positive 0.882 0.892 0.887 909\n", - "\n", - " accuracy 0.886 1821\n", - " macro avg 0.886 0.886 0.886 1821\n", - "weighted avg 0.886 0.886 0.886 1821\n", - "\n", - "CPU times: user 15min 31s, sys: 34.3 s, total: 16min 6s\n", - "Wall time: 16min\n" - ] - } - ], - "source": [ - "%%time\n", - "_ = sst.experiment(\n", - " SST_HOME,\n", - " elmo_fine_tune_phi,\n", - " fit_optimized_elmo_rnn,\n", - " train_reader=(sst.train_reader, sst.dev_reader),\n", - " assess_reader=sst.test_reader,\n", - " class_func=sst.binary_class_func,\n", - " vectorize=False) # Pass in the BERT hidden state directly!" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/evaluation_methods.ipynb b/evaluation_methods.ipynb index 36a7b10..8528418 100644 --- a/evaluation_methods.ipynb +++ b/evaluation_methods.ipynb @@ -18,7 +18,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -1023,9 +1023,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/evaluation_metrics.ipynb b/evaluation_metrics.ipynb index 325fb53..b50f8df 100644 --- a/evaluation_metrics.ipynb +++ b/evaluation_metrics.ipynb @@ -18,7 +18,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -3961,9 +3961,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/finetuning.ipynb b/finetuning.ipynb new file mode 100644 index 0000000..482dd4f --- /dev/null +++ b/finetuning.ipynb @@ -0,0 +1,1007 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Bringing contextual word representations into your models" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "__author__ = \"Christopher Potts\"\n", + "__version__ = \"CS224u, Stanford, Spring 2021\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Contents\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Overview\n", + "\n", + "This notebook provides a basic introduction to using pre-trained [BERT](https://github.com/google-research/bert) representations with the Hugging Face library. It is meant as a practical companion to our lecture on contextual word representations. The goal of this notebook is just to help you use these representations in your own work.\n", + "\n", + "If you haven't already, I encourage you to review the notebook [vsm_04_contextualreps.ipynb](vsm_04_contextualreps.ipynb) before working with this one. That notebook covers the fundamentals of these models; this one dives into the details more quickly.\n", + "\n", + "A number of the experiments in this notebook are resource-intensive. I've included timing information for the expensive steps, to give you a sense for how long things are likely to take. I ran this notebook on a laptop with a single NVIDIA RTX 2080 GPU. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## General set-up\n", + "\n", + "The following are requirements that you'll already have met if you've been working in this repository. As you can see, we'll use the [Stanford Sentiment Treebank](sst_01_overview.ipynb) for illustrations, and we'll try out a few different deep learning models." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "from sklearn.metrics import classification_report\n", + "import torch\n", + "import torch.nn as nn\n", + "from transformers import BertModel, BertTokenizer\n", + "\n", + "from torch_shallow_neural_classifier import TorchShallowNeuralClassifier\n", + "from torch_rnn_classifier import TorchRNNModel\n", + "from torch_rnn_classifier import TorchRNNClassifier\n", + "from torch_rnn_classifier import TorchRNNClassifierModel\n", + "from torch_rnn_classifier import TorchRNNClassifier\n", + "import sst\n", + "import utils" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "utils.fix_random_seeds()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "SST_HOME = os.path.join(\"data\", \"sentiment\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `transformers` library does a lot of logging. To avoid ending up with a cluttered notebook, I am changing the logging level. You might want to skip this as you scale up to building production systems, since the logging is very good – it gives you a lot of insights into what the models and code are doing." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import logging\n", + "logger = logging.getLogger()\n", + "logger.level = logging.ERROR" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Hugging Face BERT models and tokenizers\n", + "\n", + "We'll illustrate with the BERT-base cased model:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "weights_name = 'bert-base-cased'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There are lots other options for pretrained weights. See [this Hugging Face directory](https://huggingface.co/models)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we specify a tokenizer and a model that match both each other and our choice of pretrained weights:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "bert_tokenizer = BertTokenizer.from_pretrained(weights_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "bert_model = BertModel.from_pretrained(weights_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For modeling (as opposed to creating static representations), we will mostly process examples in batches – generally very small ones, as these models consume _a lot_ of memory. Here's a small batch of texts to use as the starting point for illustrations:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "example_texts = [\n", + " \"Encode sentence 1. [SEP] And sentence 2!\",\n", + " \"Bert knows Snuffleupagus\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will often need to pad (and perhaps truncate) token lists so that we can work with fixed-dimensional tensors: The `batch_encode_plus` has a lot of options for doing this:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "example_ids = bert_tokenizer.batch_encode_plus(\n", + " example_texts,\n", + " add_special_tokens=True,\n", + " return_attention_mask=True,\n", + " padding='longest')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['input_ids', 'token_type_ids', 'attention_mask'])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "example_ids.keys()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `token_type_ids` is used for multi-text inputs like NLI. The `'input_ids'` field gives the indices for each of the two examples:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[[101, 13832, 13775, 5650, 122, 119, 102, 1262, 5650, 123, 106, 102],\n", + " [101, 15035, 3520, 156, 14787, 13327, 4455, 28026, 1116, 102, 0, 0]]" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "example_ids['input_ids']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Notice that the final two tokens of the second example are pad tokens.\n", + "\n", + "For fine-tuning, we want to avoid attending to padded tokens. The `'attention_mask'` captures the needed mask, which we'll be able to feed directly to the pretrained BERT model:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0]]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "example_ids['attention_mask']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, we can run these indices and masks through the pretrained model:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "X_example = torch.tensor(example_ids['input_ids'])\n", + "X_example_mask = torch.tensor(example_ids['attention_mask'])\n", + "\n", + "with torch.no_grad():\n", + " reps = bert_model(X_example, attention_mask=X_example_mask)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Hugging Face BERT models create a special `pooler_output` representation that is the final representation above the [CLS] extended with a single layer of parameters:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([2, 768])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reps.pooler_output.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We have two examples, each representented by a single vector of dimension 768, which is $d_{model}$ for BERT base using the notation from [the original Transformers paper](https://arxiv.org/abs/1706.03762). This is an easy basis for fine-tuning, as we will see.\n", + "\n", + "We can also access the final output for each state:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([2, 12, 768])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reps.last_hidden_state.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here, we have 2 examples, each padded to the length of the longer one (12), and each of those representations has dimension 768. These representations can be used for sequence modeling, or pooled somehow for simple classifiers." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Those are all the essential ingredients for working with these parameters in Hugging Face. Of course, the library has a lot of other functionality, but the above suffices to featurize and to fine-tune." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## BERT featurization with Hugging Face\n", + "\n", + "To start, we'll use the Hugging Face interfaces just to featurize examples to create inputs to a separate model. In this setting, the BERT parameters are frozen." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "def bert_phi(text):\n", + " input_ids = bert_tokenizer.encode(text, add_special_tokens=True)\n", + " X = torch.tensor([input_ids])\n", + " with torch.no_grad():\n", + " reps = bert_model(X)\n", + " return reps.last_hidden_state.squeeze(0).numpy()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Simple feed-forward experiment\n", + "\n", + "For a simple feed-forward experiment, we can get the representation of the `[CLS]` tokens and use them as the inputs to a shallow neural network:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "def bert_classifier_phi(text):\n", + " reps = bert_phi(text)\n", + " #return reps.mean(axis=0) # Another good, easy option.\n", + " return reps[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next we read in the SST train and dev splits:" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "train = sst.train_reader(SST_HOME)\n", + "\n", + "dev = sst.dev_reader(SST_HOME)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Split the input/output pairs out into separate lists:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "X_str_train = train.sentence.values\n", + "y_train = train.label.values\n", + "\n", + "X_str_dev = dev.sentence.values\n", + "y_dev = dev.label.values" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the next step, we featurize all of the examples. These steps are likely to be the slowest in these experiments:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 3h 3min 16s, sys: 1h 9min 9s, total: 4h 12min 26s\n", + "Wall time: 35min 24s\n" + ] + } + ], + "source": [ + "%time X_train = [bert_classifier_phi(text) for text in X_str_train]" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 20min 28s, sys: 6min 30s, total: 26min 59s\n", + "Wall time: 4min 7s\n" + ] + } + ], + "source": [ + "%time X_dev = [bert_classifier_phi(text) for text in X_str_dev]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that all the examples are featurized, we can fit a model and evaluate it:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "model = TorchShallowNeuralClassifier(\n", + " early_stopping=True,\n", + " hidden_dim=300)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Stopping after epoch 23. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 5.422645628452301" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 9.19 s, sys: 355 ms, total: 9.55 s\n", + "Wall time: 3.09 s\n" + ] + } + ], + "source": [ + "%time _ = model.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "preds = model.predict(X_dev)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " negative 0.732 0.741 0.736 428\n", + " neutral 0.397 0.135 0.202 229\n", + " positive 0.659 0.876 0.752 444\n", + "\n", + " accuracy 0.669 1101\n", + " macro avg 0.596 0.584 0.564 1101\n", + "weighted avg 0.633 0.669 0.632 1101\n", + "\n" + ] + } + ], + "source": [ + "print(classification_report(y_dev, preds, digits=3))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### A feed-forward experiment with the sst module\n", + "\n", + "It is straightforward to conduct experiments like the above using `sst.experiment`, which will enable you to do a wider range of experiments without writing or copy-pasting a lot of code. " + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "def fit_shallow_network(X, y):\n", + " mod = TorchShallowNeuralClassifier(\n", + " hidden_dim=300,\n", + " early_stopping=True)\n", + " mod.fit(X, y)\n", + " return mod" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Stopping after epoch 40. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 5.189640045166016" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " negative 0.726 0.757 0.741 428\n", + " neutral 0.412 0.175 0.245 229\n", + " positive 0.688 0.865 0.766 444\n", + "\n", + " accuracy 0.679 1101\n", + " macro avg 0.609 0.599 0.584 1101\n", + "weighted avg 0.646 0.679 0.648 1101\n", + "\n", + "CPU times: user 3h 25min 19s, sys: 1h 14min 58s, total: 4h 40min 17s\n", + "Wall time: 39min 33s\n" + ] + } + ], + "source": [ + "%%time\n", + "_ = sst.experiment(\n", + " sst.train_reader(SST_HOME),\n", + " bert_classifier_phi,\n", + " fit_shallow_network,\n", + " assess_dataframes=sst.dev_reader(SST_HOME),\n", + " vectorize=False) # Pass in the BERT reps directly!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### An RNN experiment with the sst module\n", + "\n", + "We can also use BERT representations as the input to an RNN. There is just one key change from how we used these models before:\n", + "\n", + "* Previously, we would feed in lists of tokens, and they would be converted to indices into a fixed embedding space. This presumes that all words have the same representation no matter what their context is. \n", + "\n", + "* With BERT, we skip the embedding entirely and just feed in lists of BERT vectors, which means that the same word can be represented in different ways.\n", + "\n", + "`TorchRNNClassifier` supports this via `use_embedding=False`. In turn, you needn't supply a vocabulary:" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "def fit_rnn(X, y):\n", + " mod = TorchRNNClassifier(\n", + " vocab=[],\n", + " early_stopping=True,\n", + " use_embedding=False) # Pass in the BERT hidden states directly!\n", + " mod.fit(X, y)\n", + " return mod" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Stopping after epoch 35. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.5038421787321568" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " negative 0.708 0.687 0.698 428\n", + " neutral 0.355 0.328 0.341 229\n", + " positive 0.726 0.777 0.751 444\n", + "\n", + " accuracy 0.649 1101\n", + " macro avg 0.597 0.597 0.596 1101\n", + "weighted avg 0.642 0.649 0.645 1101\n", + "\n", + "CPU times: user 3h 26min 32s, sys: 1h 15min 19s, total: 4h 41min 51s\n", + "Wall time: 39min 59s\n" + ] + } + ], + "source": [ + "%%time\n", + "_ = sst.experiment(\n", + " sst.train_reader(SST_HOME),\n", + " bert_phi,\n", + " fit_rnn,\n", + " assess_dataframes=sst.dev_reader(SST_HOME),\n", + " vectorize=False) # Pass in the BERT hidden states directly!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## BERT fine-tuning with Hugging Face\n", + "\n", + "The above experiments are quite successful – BERT gives us a reliable boost compared to other methods we've explored for the SST task. However, we might expect to do even better if we fine-tune the BERT parameters as part of fitting our SST classifier. To do that, we need to incorporate the Hugging Face BERT model into our classifier. This too is quite straightforward." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### HfBertClassifier\n", + "\n", + "The most important step is to create an `nn.Module` subclass that has, for its parameters, both the BERT model and parameters for our own classifier. Here we define a very simple fine-tuning set-up in which some layers built on top of the output corresponding to `[CLS]` are used as the basis for the SST classifier:" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "class HfBertClassifierModel(nn.Module):\n", + " def __init__(self, n_classes, weights_name='bert-base-cased'):\n", + " super().__init__()\n", + " self.n_classes = n_classes\n", + " self.weights_name = weights_name\n", + " self.bert = BertModel.from_pretrained(self.weights_name)\n", + " self.bert.train()\n", + " self.hidden_dim = self.bert.embeddings.word_embeddings.embedding_dim\n", + " # The only new parameters -- the classifier:\n", + " self.classifier_layer = nn.Linear(\n", + " self.hidden_dim, self.n_classes)\n", + "\n", + " def forward(self, indices, mask):\n", + " reps = self.bert(\n", + " indices, attention_mask=mask)\n", + " return self.classifier_layer(reps.pooler_output)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As you can see, `self.bert` does the heavy-lifting: it reads in all the pretrained BERT parameters, and I've specified `self.bert.train()` just to make sure that these parameters can be updated during our training process. \n", + "\n", + "In `forward`, `self.bert` is used to process inputs, and then `pooler_output` is fed into `self.classifier_layer`. Hugging Face has already added a layer on top of the actual output for `[CLS]`, so we can specify the model as\n", + "\n", + "$$\n", + "\\begin{align}\n", + "[h_{1}, \\ldots, h_{n}] &= \\text{BERT}([x_{1}, \\ldots, x_{n}]) \\\\\n", + "h &= \\tanh(h_{1}W_{hh} + b_{h}) \\\\\n", + "y &= \\textbf{softmax}(hW_{hy} + b_{y})\n", + "\\end{align}$$\n", + "\n", + "for a tokenized input sequence $[x_{1}, \\ldots, x_{n}]$. \n", + "\n", + "The Hugging Face documentation somewhat amusingly says, of `pooler_output`,\n", + "\n", + "> This output is usually _not_ a good summary of the semantic content of the input, you're often better with averaging or pooling the sequence of hidden-states for the whole input sequence.\n", + "\n", + "which is entirely reasonable, but it will require more resources, so we'll do the simpler thing here." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For the training and prediction interface, we can subclass `TorchShallowNeuralClassifier` so that we don't have to write any of our own data-handling, training, or prediction code. The central changes are using `HfBertClassifierModel` in `build_graph` and processing the data with `batch_encode_plus`." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "class HfBertClassifier(TorchShallowNeuralClassifier):\n", + " def __init__(self, weights_name, *args, **kwargs):\n", + " self.weights_name = weights_name\n", + " self.tokenizer = BertTokenizer.from_pretrained(self.weights_name)\n", + " super().__init__(*args, **kwargs)\n", + " self.params += ['weights_name']\n", + "\n", + " def build_graph(self):\n", + " return HfBertClassifierModel(self.n_classes_, self.weights_name)\n", + "\n", + " def build_dataset(self, X, y=None):\n", + " data = self.tokenizer.batch_encode_plus(\n", + " X,\n", + " max_length=None,\n", + " add_special_tokens=True,\n", + " padding='longest',\n", + " return_attention_mask=True)\n", + " indices = torch.tensor(data['input_ids'])\n", + " mask = torch.tensor(data['attention_mask'])\n", + " if y is None:\n", + " dataset = torch.utils.data.TensorDataset(indices, mask)\n", + " else:\n", + " self.classes_ = sorted(set(y))\n", + " self.n_classes_ = len(self.classes_)\n", + " class2index = dict(zip(self.classes_, range(self.n_classes_)))\n", + " y = [class2index[label] for label in y]\n", + " y = torch.tensor(y)\n", + " dataset = torch.utils.data.TensorDataset(indices, mask, y)\n", + " return dataset" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### HfBertClassifier experiment\n", + "\n", + "That's it! Let's see how we do on the SST binary, root-only problem. Because fine-tuning is expensive, we'll conduct a modest hyperparameter search and run the model for just one epoch per setting evaluation, as we did when [assessing NLI models](nli_02_models.ipynb)." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "def bert_fine_tune_phi(text):\n", + " return text" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "def fit_hf_bert_classifier_with_hyperparameter_search(X, y):\n", + " basemod = HfBertClassifier(\n", + " weights_name='bert-base-cased',\n", + " batch_size=8, # Small batches to avoid memory overload.\n", + " max_iter=1, # We'll search based on 1 iteration for efficiency.\n", + " n_iter_no_change=5, # Early-stopping params are for the\n", + " early_stopping=True) # final evaluation.\n", + "\n", + " param_grid = {\n", + " 'gradient_accumulation_steps': [1, 4, 8],\n", + " 'eta': [0.00005, 0.0001, 0.001],\n", + " 'hidden_dim': [100, 200, 300]}\n", + "\n", + " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", + " X, y, basemod, cv=3, param_grid=param_grid)\n", + "\n", + " return bestmod" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Finished epoch 1 of 1; error is 96.940810058265926" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Best params: {'eta': 0.0001, 'gradient_accumulation_steps': 8, 'hidden_dim': 300}\n", + "Best score: 0.586\n", + " precision recall f1-score support\n", + "\n", + " negative 0.715 0.808 0.759 428\n", + " neutral 0.700 0.031 0.059 229\n", + " positive 0.662 0.905 0.765 444\n", + "\n", + " accuracy 0.686 1101\n", + " macro avg 0.692 0.581 0.527 1101\n", + "weighted avg 0.691 0.686 0.616 1101\n", + "\n", + "CPU times: user 1h 48min 23s, sys: 5min 23s, total: 1h 53min 47s\n", + "Wall time: 1h 55min 41s\n" + ] + } + ], + "source": [ + "%%time\n", + "bert_classifier_xval = sst.experiment(\n", + " sst.train_reader(SST_HOME),\n", + " bert_fine_tune_phi,\n", + " fit_hf_bert_classifier_with_hyperparameter_search,\n", + " assess_dataframes=sst.dev_reader(SST_HOME),\n", + " vectorize=False) # Pass in the BERT hidden state directly!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And now on to the final test-set evaluation, using the best model from above:" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "optimized_bert_classifier = bert_classifier_xval['model']" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "# Remove the rest of the experiment results to clear out some memory:\n", + "del bert_classifier_xval" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "def fit_optimized_hf_bert_classifier(X, y):\n", + " optimized_bert_classifier.max_iter = 1000\n", + " optimized_bert_classifier.fit(X, y)\n", + " return optimized_bert_classifier" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "test_df = sst.sentiment_reader(\n", + " os.path.join(SST_HOME, \"sst3-test-labeled.csv\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Stopping after epoch 9. Validation score did not improve by tol=1e-05 for more than 5 epochs. Final error is 7.519404984079301" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " negative 0.756 0.825 0.789 912\n", + " neutral 0.338 0.314 0.325 389\n", + " positive 0.821 0.771 0.795 909\n", + "\n", + " accuracy 0.713 2210\n", + " macro avg 0.638 0.636 0.636 2210\n", + "weighted avg 0.709 0.713 0.710 2210\n", + "\n", + "CPU times: user 13min 7s, sys: 19 s, total: 13min 26s\n", + "Wall time: 13min 27s\n" + ] + } + ], + "source": [ + "%%time\n", + "_ = sst.experiment(\n", + " sst.train_reader(SST_HOME),\n", + " bert_fine_tune_phi,\n", + " fit_optimized_hf_bert_classifier,\n", + " assess_dataframes=test_df,\n", + " vectorize=False) # Pass in the BERT hidden state directly!" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/hw_colors.ipynb b/hw_colors.ipynb index b02808e..15ea87d 100644 --- a/hw_colors.ipynb +++ b/hw_colors.ipynb @@ -9,12 +9,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -77,16 +77,18 @@ "from nltk.translate.bleu_score import corpus_bleu\n", "import numpy as np\n", "import os\n", + "import pandas as pd\n", "from sklearn.model_selection import train_test_split\n", - "from torch_color_describer import (\n", - " ContextualColorDescriber, create_example_dataset)\n", + "from torch_color_describer import ContextualColorDescriber\n", + "from torch_color_describer import create_example_dataset\n", + "\n", "import utils\n", "from utils import START_SYMBOL, END_SYMBOL, UNK_SYMBOL" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -95,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -114,7 +116,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -126,7 +128,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -142,9 +144,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "13890" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "len(dev_examples)" ] @@ -167,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -192,7 +205,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -213,7 +226,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -226,9 +239,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['', 'aqua,', 'teal', '']" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "tokenize_example(dev_texts_train[376])" ] @@ -250,7 +274,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -267,11 +291,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ - "test_tokenize_example(tokenize_example)" + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_tokenize_example(tokenize_example)" ] }, { @@ -290,7 +315,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -308,7 +333,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -328,9 +353,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1439" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "len(dev_vocab)" ] @@ -348,7 +384,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -368,9 +404,22 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[[0.19444444444444445, 0.5, 0.11],\n", + " [0.7472222222222222, 0.5, 0.27],\n", + " [0.2722222222222222, 0.5, 0.73]]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "represent_color_context(dev_rawcols_train[0])" ] @@ -386,21 +435,22 @@ "* You are not required to keep `represent_color`. This might be unnatural if you want to perform an operation on each color trio all at once.\n", "* For that matter, if you want to process all of the color contexts in the entire data set all at once, that is fine too, as long as you can also perform the operation at test time with an unknown number of examples being tested.\n", "\n", - "* The Fourier-transform method of [Monroe et al. 2017](https://transacl.org/ojs/index.php/tacl/article/view/1142) is a proven choice for our task. __It is not required that you implement this.__ However, if you decide to, you might find that the overly terse presentation in the paper is an obstacle. They key thing to see is that the notation $\\hat{f}_{jkl}$ is meant to specify a full coordinate system. Thus, you might do something like\n", + "* The Fourier-transform method of [Monroe et al. 2016](https://www.aclweb.org/anthology/D16-1243/) and [Monroe et al. 2017](https://transacl.org/ojs/index.php/tacl/article/view/1142) is a proven choice for our task. __It is not required that you implement this.__ However, if you decide to, you might find that the overly terse presentation in the paper is an obstacle. They key thing to see is that the notation $\\hat{f}_{jkl}$ is meant to specify a full coordinate system. Thus, you might do something like\n", "\n", " ```\n", "from itertools import product\n", "for j, k, l in product((0, 1, 2), repeat=3): \n", " f_jkl = ...\n", "```\n", - "and collect these `f_jkl` values in a list of 27 values. Additionally, in Python, [`2j` produces a value with `real` and `imag` attributes](https://docs.python.org/3.7/library/cmath.html). Each element `f_jkl` should have these components. If you concatenate the `real` and `imag` parts of all the `f_jkl`, you will have a 54-dimensional representation, as in the paper. Remember to start with an HSV representation, and with $h$ in $[0, 360]$, $s$ in $[0, 200]$, and $v$ in $[0, 200]$ (or else do the scaling differently). Note that the values in our corpus are in HLS format, [which are easily converted to HSV](https://en.wikipedia.org/wiki/HSL_and_HSV#HSV_to_HSL).\n", + "\n", + " and collect these `f_jkl` values in a list of 27 values. Additionally, in Python, [`2j` produces a value with `real` and `imag` attributes](https://docs.python.org/3.7/library/cmath.html). Each element `f_jkl` should have these components. If you concatenate the `real` and `imag` parts of all the `f_jkl`, you will have a 54-dimensional representation, as in the paper. Remember to start with an HSV representation, and with $h$ in $[0, 360]$, $s$ in $[0, 200]$, and $v$ in $[0, 200]$ (or else do the scaling differently). Note that the values in our corpus are in HLS format, [which are easily converted to HSV](https://en.wikipedia.org/wiki/HSL_and_HSV#HSV_to_HSL).\n", "\n", "The following test seeks to ensure only that the output of your `represent_color_context` will be compatible with the models we are creating:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -422,11 +472,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ - "test_represent_color_context(represent_color_context)" + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_represent_color_context(represent_color_context)" ] }, { @@ -445,7 +496,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -472,7 +523,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -483,9 +534,25 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Stopping after epoch 15. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 49.4446759223938" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 1min 47s, sys: 4.92 s, total: 1min 52s\n", + "Wall time: 57 s\n" + ] + } + ], "source": [ "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", " %time _ = dev_mod.fit(dev_cols_train, dev_seqs_train)\n", @@ -502,11 +569,177 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "dev_mod.evaluate(dev_cols_test, dev_seqs_test)" + "evaluation = dev_mod.evaluate(dev_cols_test, dev_seqs_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['listener_accuracy', 'corpus_bleu', 'target_index', 'predicted_index', 'predicted_utterances'])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.34177944140512523" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation['listener_accuracy']" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.34177944140512523" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dev_mod.listener_accuracy(dev_cols_test, dev_seqs_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.46928501136332795" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation['corpus_bleu']" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.46928501136332795" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bleu, predicted_utterances = dev_mod.corpus_bleu(dev_cols_test, dev_seqs_test)\n", + "\n", + "bleu" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[2, 2, 2, 2, 2]" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation['target_index'][: 5]" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[2, 2, 1, 1, 1]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation['predicted_index'][: 5]" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[['', 'light', ''],\n", + " ['', 'light', ''],\n", + " ['', 'light', ''],\n", + " ['', 'light', ''],\n", + " ['', 'light', '']]" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "evaluation['predicted_utterance'][: 5]" ] }, { @@ -518,20 +751,42 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[['', 'light', '']]" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "dev_mod.predict(dev_cols_test[:1])" + "dev_mod.predict(dev_cols_test[: 1])" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[['', 'right', 'side', '###', 'purple', 'pinkish', '']]" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "dev_seqs_test[:1]" + "dev_seqs_test[: 1]" ] }, { @@ -606,7 +861,8 @@ "metadata": {}, "outputs": [], "source": [ - "test_create_glove_embedding(create_glove_embedding)" + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_create_glove_embedding(create_glove_embedding)" ] }, { @@ -833,7 +1089,8 @@ "metadata": {}, "outputs": [], "source": [ - "test_get_embeddings(ColorContextDecoder)" + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_get_embeddings(ColorContextDecoder)" ] }, { @@ -977,18 +1234,18 @@ "source": [ "There are many options for your original system, which consists of the full pipeline – all preprocessing and modeling steps. You are free to use any model you like, as long as you subclass `ContextualColorDescriber` in a way that allows its `evaluate` method to behave in the expected way.\n", "\n", - "So that we can evaluate models in a uniform way for the bake-off, we ask that you modify the function `my_original_system` below so that it accepts a trained instance of your model and does any preprocessing steps required by your model.\n", + "So that we can evaluate models in a uniform way for the bake-off, we ask that you modify the function `evaluate_original_system` below so that it accepts a trained instance of your model and does any preprocessing steps required by your model.\n", "\n", - "If we seek to reproduce your results, we will rerun this entire notebook. Thus, it is fine if your `my_original_system` makes use of functions you wrote or modified above this cell." + "If we seek to reproduce your results, we will rerun this entire notebook. Thus, it is fine if your `evaluate_original_system` makes use of functions you wrote or modified above this cell." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "metadata": {}, "outputs": [], "source": [ - "def my_original_system(trained_model, color_seqs_test, texts_test):\n", + "def evaluate_original_system(trained_model, color_seqs_test, texts_test):\n", " \"\"\"\n", " Feel free to modify this code to accommodate the needs of\n", " your system. Just keep in mind that it will get raw corpus\n", @@ -1004,28 +1261,70 @@ "\n", "\n", " # Optionally include other preprocessing steps here. Note:\n", - " # DO NOT RETRAIN YOUR MODEL! It's a tempting step, but it's\n", - " # a mistake and will get you disqualified!\n", - "\n", + " # DO NOT RETRAIN YOUR MODEL AS PART OF THIS EVALUATION!\n", + " # It's a tempting step, but it's a mistake and will get\n", + " # you disqualified!\n", "\n", " # The following core score calculations are required:\n", - " return trained_model.evaluate(col_seqs, tok_seqs)" + " evaluation = trained_model.evaluate(col_seqs, tok_seqs)\n", + "\n", + " return evaluation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "If `my_original_system` works on test sets you create from the corpus distribution, then it will work for the bake-off, so consider checking that. For example, this would check that `dev_mod` above passes muster:" + "If `evaluate_original_system` works on test sets you create from the corpus distribution, then it will work for the bake-off, so consider checking that. For example, this would check that `dev_mod` above passes muster:" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ - "my_original_system(dev_mod, dev_rawcols_test, dev_texts_test)" + "my_evaluation = evaluate_original_system(dev_mod, dev_rawcols_test, dev_texts_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.34177944140512523" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "my_evaluation['listener_accuracy']" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.46928501136332795" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "my_evaluation['corpus_bleu']" ] }, { @@ -1049,7 +1348,7 @@ "# You should report your score as a decimal value <=1.0\n", "# PLEASE MAKE SURE NOT TO DELETE OR EDIT THE START AND STOP COMMENTS\n", "\n", - "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM \n", + "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM\n", "# SHOULD BE ADDED BELOW THE 'IS_GRADESCOPE_ENV' CHECK CONDITION. DOING\n", "# SO ABOVE THE CHECK MAY CAUSE THE AUTOGRADER TO FAIL.\n", "\n", @@ -1072,50 +1371,64 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For the bake-off, we will release a test set. You will evaluate your custom model from the previous question on these new datasets using your `my_original_system` function. Rules:\n", - "\n", - "1. Only one evaluation is permitted.\n", - "1. No additional system tuning is permitted once the bake-off has started.\n", + "For the bake-off, we will use our original test set. The function you need to run for the submission is the following, which uses your `evaluate_original_system` from above:" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "def create_bakeoff_submission(\n", + " trained_model,\n", + " output_filename='cs224u-sentiment-bakeoff-entry.csv'):\n", + " bakeoff_src_filename = os.path.join(\n", + " \"data\", \"colors\", \"cs224u-colors-test.csv\")\n", "\n", - "Systems will be ranked primarily by `listener_accuracy`, but we will also consider their `corpus_bleu` scores as reported by `my_original_system`. However, the BLEU score is just a simple check that your system is speaking some version of English that corresponds in some meaningful way to the gold descriptions, so you should concentrate on `listener_accuracy`.\n", + " bakeoff_corpus = ColorsCorpusReader(bakeoff_src_filename)\n", "\n", - "The cells below this one constitute your bake-off entry.\n", + " # This code just extracts the colors and texts from the new corpus:\n", + " bakeoff_rawcols, bakeoff_texts = zip(*[\n", + " [ex.colors, ex.contents] for ex in bakeoff_corpus.read()])\n", "\n", - "People who enter will receive the additional homework point, and people whose systems achieve the top score will receive an additional 0.5 points. We will test the top-performing systems ourselves, and only systems for which we can reproduce the reported results will win the extra 0.5 points.\n", + " # Original system function call; `trained_model` is your trained model:\n", + " evaluation = evaluate_original_system(\n", + " trained_model, bakeoff_rawcols, bakeoff_texts)\n", "\n", - "Late entries will be accepted, but they cannot earn the extra 0.5 points. Similarly, you cannot win the bake-off unless your homework is submitted on time.\n", + " evaluation['bakeoff_texts'] = bakeoff_texts\n", "\n", - "The announcement will include the details on where to submit your entry." + " df = pd.DataFrame(evaluation)\n", + " df.to_csv(output_filename)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 51, "metadata": {}, "outputs": [], "source": [ - "# Enter your bake-off assessment code in this cell.\n", - "# Please do not remove this comment.\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - " # Please enter your code in the scope of the above conditional.\n", - " ##### YOUR CODE HERE\n" + "create_bakeoff_submission(dev_mod)" ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "# On an otherwise blank line in this cell, please enter\n", - "# the return value of `my_original_system` from your\n", - "# bake-off run. You can just paste it in.\n", - "# Please do not remove this comment.\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - " # Please paste in your results in the scope of the above conditional.\n", - " ##### YOUR SCORE HERE\n" + "This creates a file `cs224u-sentiment-bakeoff-entry.csv` in the current directory. That file should be uploaded as-is. Please do not change its name.\n", + "\n", + "Only one upload per team is permitted, and you should do no tuning of your system based on what you see in the file – you should not study that file in anyway, beyond perhaps checking that it contains what you expected it to contain. The upload function will do some additional checking to ensure that your file is well-formed.\n", + "\n", + "The nature of our evaluation is such that we have to release the full test set with all labels. Thus, we have to trust you not to make any use of the test set during development. Recall:\n", + "\n", + "1. Only one evaluation is permitted.\n", + "1. No additional system tuning is permitted once the bake-off has started.\n", + "\n", + "Systems will be ranked primarily by `listener_accuracy`, but we will also consider their `corpus_bleu` scores. However, the BLEU score is just a simple check that your system is speaking some version of English that corresponds in some meaningful way to the gold descriptions, so you should concentrate on `listener_accuracy`.\n", + "\n", + "People who enter will receive the additional homework point, and people whose systems achieve the top score will receive an additional 0.5 points. We will test the top-performing systems ourselves, and only systems for which we can reproduce the reported results will win the extra 0.5 points.\n", + "\n", + "Late entries will be accepted, but they cannot earn the extra 0.5 points." ] } ], @@ -1135,9 +1448,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.7" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/hw_sentiment.ipynb b/hw_sentiment.ipynb new file mode 100644 index 0000000..208825d --- /dev/null +++ b/hw_sentiment.ipynb @@ -0,0 +1,944 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Homework and bake-off: Sentiment analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "__author__ = \"Christopher Potts\"\n", + "__version__ = \"CS224u, Stanford, Spring 2021\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Contents\n", + "\n", + "1. [Overview](#Overview)\n", + "1. [Methodological note](#Methodological-note)\n", + "1. [Set-up](#Set-up)\n", + "1. [Train set](#Train-set)\n", + "1. [Dev sets](#Dev-sets)\n", + "1. [A softmax baseline](#A-softmax-baseline)\n", + "1. [RNNClassifier wrapper](#RNNClassifier-wrapper)\n", + "1. [Error analysis](#Error-analysis)\n", + "1. [Homework questions](#Homework-questions)\n", + " 1. [Token-level differences [1 point]](#Token-level-differences-[1-point])\n", + " 1. [Training on some of the bakeoff data [1 point]](#Training-on-some-of-the-bakeoff-data-[1-point])\n", + " 1. [A more powerful vector-averaging baseline [2 points]](#A-more-powerful-vector-averaging-baseline-[2-points])\n", + " 1. [BERT encoding [2 points]](#BERT-encoding-[2-points])\n", + " 1. [Your original system [3 points]](#Your-original-system-[3-points])\n", + "1. [Bakeoff [1 point]](#Bakeoff-[1-point])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Overview\n", + "\n", + "This homework and associated bakeoff are devoted to supervised sentiment analysis using the ternary (positive/negative/neutral) version of the Stanford Sentiment Treebank (SST-3) as well as a new dev/test dataset drawn from restaurant reviews. Our goal in introducing the new dataset is to push you to create a system that performs well in both the movie and restaurant domains.\n", + "\n", + "The homework questions ask you to implement some baseline system, and the bakeoff challenge is to define a system that does well at both the SST-3 test set and the new restaurant test set. Both are ternary tasks, and our central bakeoff score is the mean of the macro-FI scores for the two datasets. This assigns equal weight to all classes and datasets regardless of size.\n", + "\n", + "The SST-3 test set will be used for the bakeoff evaluation. This dataset is already publicly distributed, so we are counting on people not to cheat by developing their models on the test set. You must do all your development without using the test set at all, and then evaluate exactly once on the test set and turn in the results, with no further system tuning or additional runs. __Much of the scientific integrity of our field depends on people adhering to this honor code__. \n", + "\n", + "One of our goals for this homework and bakeoff is to encourage you to engage in __the basic development cycle for supervised models__, in which you\n", + "\n", + "1. Design a new system. We recommend starting with something simple.\n", + "1. Use `sst.experiment` to evaluate your system, using random train/test splits initially.\n", + "1. If you have time, compare your system with others using `sst.compare_models` or `utils.mcnemar`. (For discussion, see [this notebook section](sst_02_hand_built_features.ipynb#Statistical-comparison-of-classifier-models).)\n", + "1. Return to step 1, or stop the cycle and conduct a more rigorous evaluation with hyperparameter tuning and assessment on the `dev` set.\n", + "\n", + "[Error analysis](#Error-analysis) is one of the most important methods for steadily improving a system, as it facilitates a kind of human-powered hill-climbing on your ultimate objective. Often, it takes a careful human analyst just a few examples to spot a major pattern that can lead to a beneficial change to the feature representations." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Methodological note\n", + "\n", + "You don't have to use the experimental framework defined below (based on `sst`). The only constraint we need to place on your system is that it must have a `predict_one` method that can map directly from an example text to a prediction, and it must be able to make predictions without having any information beyond the text. (For example, it can't depend on knowing which task the text comes from.) See [the bakeoff section below](#Bakeoff-[1-point]) for examples of functions that conform to this specification." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set-up\n", + "\n", + "See [the first notebook in this unit](sst_01_overview.ipynb#Set-up) for set-up instructions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from collections import Counter\n", + "import numpy as np\n", + "import os\n", + "import pandas as pd\n", + "from sklearn.linear_model import LogisticRegression\n", + "import torch.nn as nn\n", + "\n", + "from torch_rnn_classifier import TorchRNNClassifier\n", + "from torch_tree_nn import TorchTreeNN\n", + "import sst\n", + "import utils" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "SST_HOME = os.path.join('data', 'sentiment')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Train set" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our primary train set is the SST-3 train set:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sst_train = sst.train_reader(SST_HOME)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sst_train.shape[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This is the train set we will use for all the regular homework questions. You are welcome to bring in new datasets for your original system. You are also free to add `include_subtrees=True`. This is very likely to lead to better systems, but it substantially increases the overall size of the dataset (from 8,544 examples to 159,274), which will in turn substantially increase the time it takes to run experiments.\n", + "\n", + "See [this notebook](sst_01_overview.ipynb) for additional details of this dataset." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dev sets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We have two development set. SST3-dev consists of sentences from movie reviews, just like SST-3 train:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sst_dev = sst.dev_reader(SST_HOME)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our new bakeoff dev set consists of sentences from restaurant reviews:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "bakeoff_dev = sst.bakeoff_dev_reader(SST_HOME)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "bakeoff_dev.sample(3, random_state=1).to_dict(orient='records')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here is the label distribution:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "bakeoff_dev.label.value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The label distribution for the corresponding test set is similar to this." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## A softmax baseline\n", + "\n", + "This example is here mainly as a reminder of how to use our experimental framework with linear models:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def unigrams_phi(text):\n", + " return Counter(text.split())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Thin wrapper around `LogisticRegression` for the sake of `sst.experiment`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def fit_softmax_classifier(X, y):\n", + " mod = LogisticRegression(\n", + " fit_intercept=True,\n", + " solver='liblinear',\n", + " multi_class='ovr')\n", + " mod.fit(X, y)\n", + " return mod" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The experimental run with some notes:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "softmax_experiment = sst.experiment(\n", + " sst.train_reader(SST_HOME), # Train on any data you like except SST-3 test!\n", + " unigrams_phi, # Free to write your own!\n", + " fit_softmax_classifier, # Free to write your own!\n", + " assess_dataframes=[sst_dev, bakeoff_dev]) # Free to change this during development!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`softmax_experiment` contains a lot of information that you can use for error analysis; see [this section below](#Error-analysis) for starter code." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## RNNClassifier wrapper\n", + "\n", + "This section illustrates how to use `sst.experiment` with `TorchRNNClassifier`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To featurize examples for an RNN, we can just get the words in order, letting the model take care of mapping them into an embedding space." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def rnn_phi(text):\n", + " return text.split()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The model wrapper gets the vocabulary using `sst.get_vocab`. If you want to use pretrained word representations in here, then you can have `fit_rnn_classifier` build that space too; see [this notebook section for details](sst_03_neural_networks.ipynb#Pretrained-embeddings). See also [torch_model_base.py](torch_model_base.py) for details on the many optimization parameters that `TorchRNNClassifier` accepts." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def fit_rnn_classifier(X, y):\n", + " sst_glove_vocab = utils.get_vocab(X, mincount=2)\n", + " mod = TorchRNNClassifier(\n", + " sst_glove_vocab,\n", + " early_stopping=True)\n", + " mod.fit(X, y)\n", + " return mod" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rnn_experiment = sst.experiment(\n", + " sst.train_reader(SST_HOME),\n", + " rnn_phi,\n", + " fit_rnn_classifier,\n", + " vectorize=False, # For deep learning, use `vectorize=False`.\n", + " assess_dataframes=[sst_dev, bakeoff_dev])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Error analysis\n", + "\n", + "This section begins to build an error-analysis framework using the dicts returned by `sst.experiment`. These have the following structure:\n", + "\n", + "```\n", + "'model': trained model\n", + "'phi': the feature function used\n", + "'train_dataset':\n", + " 'X': feature matrix\n", + " 'y': list of labels\n", + " 'vectorizer': DictVectorizer,\n", + " 'raw_examples': list of raw inputs, before featurizing \n", + "'assess_datasets': list of datasets, each with the same structure as the value of 'train_dataset'\n", + "'predictions': list of lists of predictions on the assessment datasets\n", + "'metric': `score_func.__name__`, where `score_func` is an `sst.experiment` argument\n", + "'score': the `score_func` score on the each of the assessment dataasets\n", + "```\n", + "The following function just finds mistakes, and returns a `pd.DataFrame` for easy subsequent processing:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def find_errors(experiment):\n", + " \"\"\"Find mistaken predictions.\n", + "\n", + " Parameters\n", + " ----------\n", + " experiment : dict\n", + " As returned by `sst.experiment`.\n", + "\n", + " Returns\n", + " -------\n", + " pd.DataFrame\n", + "\n", + " \"\"\"\n", + " dfs = []\n", + " for i, dataset in enumerate(experiment['assess_datasets']):\n", + " df = pd.DataFrame({\n", + " 'raw_examples': dataset['raw_examples'],\n", + " 'predicted': experiment['predictions'][i],\n", + " 'gold': dataset['y']})\n", + " df['correct'] = df['predicted'] == df['gold']\n", + " df['dataset'] = i\n", + " dfs.append(df)\n", + " return pd.concat(dfs)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "softmax_analysis = find_errors(softmax_experiment)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rnn_analysis = find_errors(rnn_experiment)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here we merge the sotmax and RNN experiments into a single DataFrame:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "analysis = softmax_analysis.merge(\n", + " rnn_analysis, left_on='raw_examples', right_on='raw_examples')\n", + "\n", + "analysis = analysis.drop('gold_y', axis=1).rename(columns={'gold_x': 'gold'})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The following code collects a specific subset of examples; small modifications to its structure will give you different interesting subsets:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Examples where the softmax model is correct, the RNN is not,\n", + "# and the gold label is 'positive'\n", + "\n", + "error_group = analysis[\n", + " (analysis['predicted_x'] == analysis['gold'])\n", + " &\n", + " (analysis['predicted_y'] != analysis['gold'])\n", + " &\n", + " (analysis['gold'] == 'positive')\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "error_group.shape[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for ex in error_group['raw_examples'].sample(5, random_state=1):\n", + " print(\"=\"*70)\n", + " print(ex)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Homework questions\n", + "\n", + "Please embed your homework responses in this notebook, and do not delete any cells from the notebook. (You are free to add as many cells as you like as part of your responses.)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Token-level differences [1 point]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can begin to get a sense for how our two dev sets differ by considering the most frequent tokens from each. This question asks you to begin such analysis.\n", + "\n", + "Your task: write a function `get_token_counts` that, given a `pd.DataFrame` in the format of our datasets, tokenizes the example sentences based on whitespace and creates a count distribution over all of the tokens. The function should return a `pd.Series` sorted by frequency; if you create a count dictionary `d`, then `pd.Series(d).sort_values(ascending=False)` will give you what you need." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def get_token_counts(df):\n", + " pass\n", + " ##### YOUR CODE HERE\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def test_get_token_counts(func):\n", + " df = pd.DataFrame([\n", + " {'sentence': 'a a b'},\n", + " {'sentence': 'a b a'},\n", + " {'sentence': 'a a a b.'}])\n", + " result = func(df)\n", + " for token, expected in (('a', 7), ('b', 2), ('b.', 1)):\n", + " actual = result.loc[token]\n", + " assert actual == expected, \\\n", + " \"For token {}, expected {}; got {}\".format(\n", + " token, expected, actual)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_get_token_counts(get_token_counts)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As you develop your original system, you might review these results. The two dev sets have different vocabularies and different low-level encoding details that are sure to impact model performance, especially when one considers that the train set is like `sst_dev` in all these respects. For additional discussion, see [this notebook section](sst_01_overview.ipynb#Tokenization)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Training on some of the bakeoff data [1 point]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We have so far presented the bakeoff dev set as purely for evaluation. Since the train set consists entirely of SST-3 data, this makes the bakeoff split especially challenging. We might be able to reduce the challenging by adding some of the bakeoff dev set to the train set, keeping some of it for evaluation. The current question asks to begin explore the effects of such training.\n", + "\n", + "Your task: write a function `run_mixed_training_experiment`. The function should:\n", + "\n", + "1. Take as inputs (a) a model training wrapper like `fit_softmax_classifier` and (b) an integer `bakeoff_train_size` specifying the number of examples from `bakeoff_dev` that should be included in the train set.\n", + "1. Split `bakeoff_dev` so that the first `bakeoff_train_size` examples are in the train set and the rest are used for evaluation.\n", + "1. Use `sst.experiment` with the user-supplied model training wrapper, `unigram_phi` as defined above, and a train set that consists of SST-3 train and the train portion of `bakeoff_dev` as defined in step 2. The value of `assess_dataframes` should be a list consisting of the SST-3 dev set and the evaluation portion of `bakeoff_dev` as defined in step 2.\n", + "1. Return the return value of `sst.experiment`.\n", + "\n", + "The function `test_run_mixed_training_experiment` will help you iterate to the required design." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def run_mixed_training_experiment(wrapper_func, bakeoff_train_size):\n", + " pass\n", + " ##### YOUR CODE HERE\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def test_run_mixed_training_experiment(func):\n", + " bakeoff_train_size = 1000\n", + " experiment = func(fit_softmax_classifier, bakeoff_train_size)\n", + "\n", + " assess_size = len(experiment['assess_datasets'])\n", + " assert len(experiment['assess_datasets']) == 2, \\\n", + " (\"The evaluation should be done on two datasets: \"\n", + " \"SST3 and part of the bakeoff dev set. \"\n", + " \"You have {} datasets.\".format(assess_size))\n", + "\n", + " bakeoff_test_size = bakeoff_dev.shape[0] - bakeoff_train_size\n", + " expected_eval_examples = bakeoff_test_size + sst_dev.shape[0]\n", + " eval_examples = sum(len(d['raw_examples']) for d in experiment['assess_datasets'])\n", + " assert expected_eval_examples == eval_examples, \\\n", + " \"Expected {} evaluation examples; got {}\".format(\n", + " expected_eval_examples, eval_examples)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_run_mixed_training_experiment(run_mixed_training_experiment)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### A more powerful vector-averaging baseline [2 points]\n", + "\n", + "In [Distributed representations as features](sst_03_neural_networks.ipynb#Distributed-representations-as-features), we looked at a baseline for the ternary SST-3 problem in which each example is modeled as the mean of its GloVe representations. A `LogisticRegression` model was used for prediction. A neural network might do better with these representations, since there might be complex relationships between the input feature dimensions that a linear classifier can't learn. To address this question, we want to get set up to run the experiment with a shallow neural classifier. \n", + "\n", + "Your task: write and submit a model wrapper function around `TorchShallowNeuralClassifier`. This function should implement hyperparameter search according to this specification:\n", + "\n", + "* Set `early_stopping=True` for all experiments.\n", + "* Using 3-fold cross-validation, exhaustively explore this set of hyperparameter combinations:\n", + " * The hidden dimensionality at 50, 100, and 200.\n", + " * The hidden activation function as `nn.Tanh()` and `nn.ReLU()`.\n", + "* For all other parameters to `TorchShallowNeuralClassifier`, use the defaults.\n", + "\n", + "See [this notebook section](sst_02_hand_built_features.ipynb#Hyperparameter-search) for examples. You are not required to run a full evaluation with this function using `sst.experiment`, but we assume you will want to.\n", + "\n", + "We're not evaluating the quality of your model. (We've specified the protocols completely, but there will still be variation in the results.) However, the primary goal of this question is to get you thinking more about this strong baseline feature representation scheme for SST-3, so we're sort of hoping you feel compelled to try out variations on your own." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from torch_shallow_neural_classifier import TorchShallowNeuralClassifier\n", + "\n", + "def fit_shallow_neural_classifier_with_hyperparameter_search(X, y):\n", + " pass\n", + " ##### YOUR CODE HERE\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### BERT encoding [2 points]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We might hypothesize that encoding our examples with BERT will yield improvements over the GloVe averaging method explored in the previous question, since BERT implements a much more complex and data-driven function for this kind of combination. This question asks you to begin exploring this general hypothesis.\n", + "\n", + "Your task: write a function `hf_cls_phi` that uses Hugging Face functionality to encode individual examples with BERT and returns the final output representation above the [CLS] token.\n", + "\n", + "You are not required to evaluate this feature function, but it is easy to do so with `sst.experiment` and `vectorize=False` (since your feature function directly encodes every example as a vector). Your code should also be a natural basis for even more powerful approaches – for example, it might be even better to pool all the output states rather than using just the first output state. Another option is [fine-tuning](finetuning.ipynb)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from transformers import BertModel, BertTokenizer\n", + "import vsm\n", + "\n", + "# Instantiate a Bert model and tokenizer based on `bert_weights_name`:\n", + "bert_weights_name = 'bert-base-uncased'\n", + "##### YOUR CODE HERE\n", + "\n", + "\n", + "def hf_cls_phi(text):\n", + " # Get the ids. `vsm.hf_encode` will help; be sure to\n", + " # set `add_special_tokens=True`.\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Get the BERT representations. `vsm.hf_represent` will help:\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Index into `reps` to get the representation above [CLS].\n", + " # The shape of `reps` should be (1, n, 768), where n is the\n", + " # number of tokens. You need the 0th element of the 2nd dim:\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # These conversions should ensure that you can work with the\n", + " # representations flexibly. Feel free to change the variable\n", + " # name:\n", + " return cls_rep.cpu().numpy()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def test_hf_cls_phi(func):\n", + " rep = func(\"Just testing!\")\n", + "\n", + " expected_shape = (768,)\n", + " result_shape = rep.shape\n", + " assert rep.shape == (768,), \\\n", + " \"Expected shape {}; got {}\".format(\n", + " expected_shape, result_shape)\n", + "\n", + " # String conversion to avoid precision errors:\n", + " expected_first_val = str(0.1709)\n", + " result_first_val = \"{0:.04f}\".format(rep[0])\n", + "\n", + " assert expected_first_val == result_first_val, \\\n", + " (\"Unexpected representation values. Expected the \"\n", + " \"first value to be {}; got {}\".format(\n", + " expected_first_val, result_first_val))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_hf_cls_phi(hf_cls_phi)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note: encoding all of SST-3 train (no subtrees) takes about 11 minutes on my 2015 iMac, CPU only (32GB)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Your original system [3 points]\n", + "\n", + "Your task is to develop an original model for the SST-3 problem and our new bakeoff dataset. There are many options. If you spend more than a few hours on this homework problem, you should consider letting it grow into your final project! Here are some relatively manageable ideas that you might try:\n", + "\n", + "1. We didn't systematically evaluate the `bidirectional` option to the `TorchRNNClassifier`. Similarly, that model could be tweaked to allow multiple LSTM layers (at present there is only one), and you could try adding layers to the classifier portion of the model as well.\n", + "\n", + "1. We've already glimpsed the power of rich initial word representations, and later in the course we'll see that smart initialization usually leads to a performance gain in NLP, so you could perhaps achieve a winning entry with a simple model that starts in a great place.\n", + "\n", + "1. Our [practical introduction to contextual word representations](finetuning.ipynb) covers pretrained representations and interfaces that are likely to boost the performance of any system.\n", + "\n", + "We want to emphasize that this needs to be an __original__ system. It doesn't suffice to download code from the Web, retrain, and submit. You can build on others' code, but you have to do something new and meaningful with it. See the course website for additional guidance on how original systems will be evaluated.\n", + "\n", + "In the cell below, please provide a brief technical description of your original system, so that the teaching team can gain an understanding of what it does. This will help us to understand your code and analyze all the submissions to identify patterns and strategies. We also ask that you report the best score your system got during development (your best average of macro-F1 scores), just to help us understand how systems performed overall." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# PLEASE MAKE SURE TO INCLUDE THE FOLLOWING BETWEEN THE START AND STOP COMMENTS:\n", + "# 1) Textual description of your system.\n", + "# 2) The code for your original system.\n", + "# 3) The score achieved by your system in place of MY_NUMBER.\n", + "# With no other changes to that line.\n", + "# You should report your score as a decimal value <=1.0\n", + "# PLEASE MAKE SURE NOT TO DELETE OR EDIT THE START AND STOP COMMENTS\n", + "\n", + "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM\n", + "# SHOULD BE ADDED BELOW THE 'IS_GRADESCOPE_ENV' CHECK CONDITION. DOING\n", + "# SO ABOVE THE CHECK MAY CAUSE THE AUTOGRADER TO FAIL.\n", + "\n", + "# START COMMENT: Enter your system description in this cell.\n", + "# My peak score was: MY_NUMBER\n", + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " pass\n", + "\n", + "# STOP COMMENT: Please do not remove this comment." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bakeoff [1 point]\n", + "\n", + "As we said above, the bakeoff evaluation data is the official SST test-set release and a new test set derived from the same sources and labeling methods as for `bakeoff_dev`.\n", + "\n", + "For this bakeoff, you'll evaluate your original system from the above homework problem on these test sets. Our metric will be the mean of the macro-F1 values, which weights both datasets equally despite their differing sizes.\n", + "\n", + "The central requirement for your system is that you have define a `predict_one` method for it that maps a text (str) directly to a label prediction – one of 'positive', 'negative', 'neutral'. If you used `sst.experiment` with `vectorize=True`, then the following function (for `softmax_experiment`) will be easy to adapt – you probably just need to change the variable `softmax_experiment` to the variable for your experiment output." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def predict_one_softmax(text):\n", + " # Singleton list of feature dicts:\n", + " feats = [softmax_experiment['phi'](text)]\n", + " # Vectorize to get a feature matrix:\n", + " X = softmax_experiment['train_dataset']['vectorizer'].transform(feats)\n", + " # Standard sklearn `predict` step:\n", + " preds = softmax_experiment['model'].predict(X)\n", + " # Be sure to return the only member of the predictions,\n", + " # rather than the singleton list:\n", + " return preds[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you used an RNN like the one we demoed above, then featurization is a bit more straightforward:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def predict_one_rnn(text):\n", + " # Singleton list of feature dicts:\n", + " feats = [rnn_experiment['phi'](text)]\n", + " # Standard `predict` step on a list of lists of str:\n", + " preds = rnn_experiment['model'].predict(X)\n", + " # Be sure to return the only member of the predictions,\n", + " # rather than the singleton list:\n", + " return preds[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The following function is used to create the bakeoff submission file. Its arguments are your `predict_one` function and an output filename (str)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def create_bakeoff_submission(\n", + " predict_one_func,\n", + " output_filename='cs224u-sentiment-bakeoff-entry.csv'):\n", + "\n", + " bakeoff_test = sst.bakeoff_test_reader(SST_HOME)\n", + " sst_test = sst.test_reader(SST_HOME)\n", + " bakeoff_test['dataset'] = 'bakeoff'\n", + " sst_test['dataset'] = 'sst3'\n", + " df = pd.concat((bakeoff_test, sst_test))\n", + "\n", + " df['prediction'] = df['sentence'].apply(predict_one_func)\n", + "\n", + " df.to_csv(output_filename, index=None)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Thus, for example, the following will create a bake-off entry based on `predict_one_softmax`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "create_bakeoff_submission(predict_one_softmax)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This creates a file `cs224u-sentiment-bakeoff-entry.csv` in the current directory. That file should be uploaded as-is. Please do not change its name.\n", + "\n", + "Only one upload per team is permitted, and you should do no tuning of your system based on what you see in our bakeoff prediction file – you should not study that file in anyway, beyond perhaps checking that it contains what you expected it to contain. The upload function will do some additional checking to ensure that your file is well-formed.\n", + "\n", + "People who enter will receive the additional homework point, and people whose systems achieve the top score will receive an additional 0.5 points. We will test the top-performing systems ourselves, and only systems for which we can reproduce the reported results will win the extra 0.5 points.\n", + "\n", + "Late entries will be accepted, but they cannot earn the extra 0.5 points." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + }, + "widgets": { + "state": {}, + "version": "1.1.2" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/hw_sst.ipynb b/hw_sst.ipynb deleted file mode 100644 index e1b212f..0000000 --- a/hw_sst.ipynb +++ /dev/null @@ -1,770 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Homework and bake-off: Stanford Sentiment Treebank" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Contents\n", - "\n", - "1. [Overview](#Overview)\n", - "1. [Methodological note](#Methodological-note)\n", - "1. [Set-up](#Set-up)\n", - "1. [A softmax baseline](#A-softmax-baseline)\n", - "1. [RNNClassifier wrapper](#RNNClassifier-wrapper)\n", - "1. [Error analysis](#Error-analysis)\n", - "1. [Homework questions](#Homework-questions)\n", - " 1. [Sentiment words alone [2 points]](#Sentiment-words-alone-[2-points])\n", - " 1. [A more powerful vector-averaging baseline [2 points]](#A-more-powerful-vector-averaging-baseline-[2-points])\n", - " 1. [Sentiment shifters [2 points]](#Sentiment-shifters-[2-points])\n", - " 1. [Your original system [3 points]](#Your-original-system-[3-points])\n", - "1. [Bake-off [1 point]](#Bake-off-[1-point])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Overview\n", - "\n", - "This homework and associated bake-off are devoted to the Stanford Sentiment Treebank (SST). The homework questions ask you to implement some baseline systems and some original feature functions, and the bake-off challenge is to define a system that does extremely well at the SST task.\n", - "\n", - "We'll focus on the ternary task as defined by `sst.ternary_class_func` This isn't used in the literature but I think it is the best version of the SST problem for the reasons given [here](sst_01_overview.ipynb#Modeling-the-SST-labels).\n", - "\n", - "The SST test set will be used for the bake-off evaluation. This dataset is already publicly distributed, so we are counting on people not to cheat by develping their models on the test set. You must do all your development without using the test set at all, and then evaluate exactly once on the test set and turn in the results, with no further system tuning or additional runs. __Much of the scientific integrity of our field depends on people adhering to this honor code__. \n", - "\n", - "Our only additional restriction is that you cannot use any of the subtree labels as input features. You can have your system learn to predict them (as intended), but no feature function can make use of them.\n", - "\n", - "One of our goals for this homework and bake-off is to encourage you to engage in __the basic development cycle for supervised models__, in which you\n", - "\n", - "1. Write a new feature function. We recommend starting with something simple.\n", - "1. Use `sst.experiment` to evaluate your new feature function, with at least `fit_softmax_classifier`.\n", - "1. If you have time, compare your feature function with `unigrams_phi` using `sst.compare_models` or `utils.mcnemar`. (For discussion, see [this notebook section](sst_02_hand_built_features.ipynb#Statistical-comparison-of-classifier-models).)\n", - "1. Return to step 1, or stop the cycle and conduct a more rigorous evaluation with hyperparameter tuning and assessment on the `dev` set.\n", - "\n", - "[Error analysis](#Error-analysis) is one of the most important methods for steadily improving a system, as it facilitates a kind of human-powered hill-climbing on your ultimate objective. Often, it takes a careful human analyst just a few examples to spot a major pattern that can lead to a beneficial change to the feature representations." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Methodological note\n", - "\n", - "You don't have to use the experimental framework defined below (based on `sst`). However, if you don't use `sst.experiment` as below, then make sure you're training only on `train`, evaluating on `dev`, and that you report with \n", - "\n", - "```\n", - "from sklearn.metrics import classification_report\n", - "classification_report(y_dev, predictions)\n", - "```\n", - "where `y_dev = [y for tree, y in sst.dev_reader(class_func=sst.ternary_class_func)]`. We'll focus on the value at `macro avg` under `f1-score` in these reports." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Set-up\n", - "\n", - "See [the first notebook in this unit](sst_01_overview.ipynb#Set-up) for set-up instructions." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from collections import Counter\n", - "from nltk.tree import Tree\n", - "import numpy as np\n", - "import os\n", - "import pandas as pd\n", - "import random\n", - "from sklearn.linear_model import LogisticRegression\n", - "import sst\n", - "import torch.nn as nn\n", - "from torch_rnn_classifier import TorchRNNClassifier\n", - "from torch_tree_nn import TorchTreeNN\n", - "import utils" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "SST_HOME = os.path.join('data', 'trees')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## A softmax baseline\n", - "\n", - "This example is here mainly as a reminder of how to use our experimental framework with linear models." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def unigrams_phi(tree):\n", - " \"\"\"The basis for a unigrams feature function.\n", - "\n", - " Parameters\n", - " ----------\n", - " tree : nltk.tree\n", - " The tree to represent.\n", - "\n", - " Returns\n", - " -------\n", - " Counter\n", - " A map from strings to their counts in `tree`. (Counter maps a\n", - " list to a dict of counts of the elements in that list.)\n", - "\n", - " \"\"\"\n", - " return Counter(tree.leaves())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Thin wrapper around `LogisticRegression` for the sake of `sst.experiment`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_softmax_classifier(X, y):\n", - " mod = LogisticRegression(\n", - " fit_intercept=True,\n", - " solver='liblinear',\n", - " multi_class='ovr')\n", - " mod.fit(X, y)\n", - " return mod" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The experimental run with some notes:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "softmax_experiment = sst.experiment(\n", - " SST_HOME,\n", - " unigrams_phi, # Free to write your own!\n", - " fit_softmax_classifier, # Free to write your own!\n", - " train_reader=sst.train_reader, # Fixed by the competition.\n", - " assess_reader=sst.dev_reader, # Fixed until the bake-off.\n", - " class_func=sst.ternary_class_func) # Fixed by the bake-off rules." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "`softmax_experiment` contains a lot of information that you can use for analysis; see [this section below](#Error-analysis) for starter code." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## RNNClassifier wrapper\n", - "\n", - "This section illustrates how to use `sst.experiment` with `TorchRNNClassifier`. The same basic patterns hold for using `TorchTreeNN`; see [sst_03_neural_networks.ipynb](sst_03_neural_networks.ipynb) for additional discussion." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To featurize examples for an RNN, we just get the words in order, letting the model take care of mapping them into an embedding space." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def rnn_phi(tree):\n", - " return tree.leaves()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The model wrapper gets the vocabulary using `sst.get_vocab`. If you want to use pretrained word representations in here, then you can have `fit_rnn_classifier` build that space too; see [this notebook section for details](sst_03_neural_networks.ipynb#Pretrained-embeddings). See also [torch_model_base.py](torch_model_base.py) for details on the many optimization parameters that `TorchRNNClassifier` accepts." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_rnn_classifier(X, y):\n", - " sst_glove_vocab = utils.get_vocab(X, mincount=2)\n", - " mod = TorchRNNClassifier(\n", - " sst_glove_vocab,\n", - " early_stopping=True)\n", - " mod.fit(X, y)\n", - " return mod" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "rnn_experiment = sst.experiment(\n", - " SST_HOME,\n", - " rnn_phi,\n", - " fit_rnn_classifier,\n", - " vectorize=False, # For deep learning, use `vectorize=False`.\n", - " assess_reader=sst.dev_reader)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Error analysis\n", - "\n", - "This section begins to build an error-analysis framework using the dicts returned by `sst.experiment`. These have the following structure:\n", - "\n", - "```\n", - "'model': trained model\n", - "'phi': the feature function used\n", - "'train_dataset':\n", - " 'X': feature matrix\n", - " 'y': list of labels\n", - " 'vectorizer': DictVectorizer,\n", - " 'raw_examples': list of raw inputs, before featurizing \n", - "'assess_dataset': same structure as the value of 'train_dataset'\n", - "'predictions': predictions on the assessment data\n", - "'metric': `score_func.__name__`, where `score_func` is an `sst.experiment` argument\n", - "'score': the `score_func` score on the assessment data\n", - "```\n", - "The following function just finds mistakes, and returns a `pd.DataFrame` for easy subsequent processing:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def find_errors(experiment):\n", - " \"\"\"Find mistaken predictions.\n", - "\n", - " Parameters\n", - " ----------\n", - " experiment : dict\n", - " As returned by `sst.experiment`.\n", - "\n", - " Returns\n", - " -------\n", - " pd.DataFrame\n", - "\n", - " \"\"\"\n", - " raw_examples = experiment['assess_dataset']['raw_examples']\n", - " raw_examples = [\" \".join(tree.leaves()) for tree in raw_examples]\n", - " df = pd.DataFrame({\n", - " 'raw_examples': raw_examples,\n", - " 'predicted': experiment['predictions'],\n", - " 'gold': experiment['assess_dataset']['y']})\n", - " df['correct'] = df['predicted'] == df['gold']\n", - " return df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "softmax_analysis = find_errors(softmax_experiment)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "rnn_analysis = find_errors(rnn_experiment)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here we merge the sotmax and RNN experiments into a single DataFrame:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "analysis = softmax_analysis.merge(\n", - " rnn_analysis, left_on='raw_examples', right_on='raw_examples')\n", - "\n", - "analysis = analysis.drop('gold_y', axis=1).rename(columns={'gold_x': 'gold'})" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The following code collects a specific subset of examples; small modifications to its structure will give you different interesting subsets:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Examples where the softmax model is correct, the RNN is not,\n", - "# and the gold label is 'positive'\n", - "\n", - "error_group = analysis[\n", - " (analysis['predicted_x'] == analysis['gold'])\n", - " &\n", - " (analysis['predicted_y'] != analysis['gold'])\n", - " &\n", - " (analysis['gold'] == 'positive')\n", - "]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "error_group.shape[0]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "for ex in error_group['raw_examples'].sample(5):\n", - " print(\"=\"*70)\n", - " print(ex)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Homework questions\n", - "\n", - "Please embed your homework responses in this notebook, and do not delete any cells from the notebook. (You are free to add as many cells as you like as part of your responses.)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Sentiment words alone [2 points]\n", - "\n", - "NLTK includes an easy interface to [Minqing Hu and Bing Liu's __Opinion Lexicon__](https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html), which consists of a list of positive words and a list of negative words. How much of the ternary SST story does this lexicon tell?\n", - "\n", - "For this problem, submit code to do the following:\n", - "\n", - "1. Create a feature function `op_unigrams_phi` on the model of `unigrams_phi` above, but filtering the vocabulary to just items that are members of the Opinion Lexicon. Submit this feature function. You can use `test_op_unigrams_phi` to check your work.\n", - "\n", - "1. Evaluate your feature function with `sst.experiment`, with all the same parameters as were used to create `softmax_experiment` in [A softmax baseline](#A-softmax-baseline) above, except of course for the feature function.\n", - "\n", - "1. Use `utils.mcnemar` to compare your feature function with the results in `softmax_experiment`. The information you need for this is in `softmax_experiment` and your own `sst.experiment` results. Submit your evaluation code. You can assume `softmax_experiment` is already in memory, but your code should create the other objects necessary for this comparison." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from nltk.corpus import opinion_lexicon\n", - "\n", - "# Use set for fast membership checking:\n", - "positive = set(opinion_lexicon.positive())\n", - "negative = set(opinion_lexicon.negative())\n", - "\n", - "def op_unigrams_phi(tree):\n", - " pass\n", - " ##### YOUR PART 1 CODE HERE\n", - "\n", - "\n", - "##### YOUR PART 2 CODE HERE\n", - "\n", - "\n", - "##### YOUR PART 3 CODE HERE\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_op_unigrams_phi(func):\n", - " tree = Tree.fromstring(\"\"\"(4 (2 NLU) (4 (2 is) (4 amazing)))\"\"\")\n", - " expected = {\"amazing\": 1}\n", - " result = func(tree)\n", - " assert result == expected, \\\n", - " (\"Error for `op_unigrams_phi`: \"\n", - " \"Got `{}` which differs from `expected` \"\n", - " \"in `test_op_unigrams_phi`\".format(result))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "test_op_unigrams_phi(op_unigrams_phi)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### A more powerful vector-averaging baseline [2 points]\n", - "\n", - "In [Distributed representations as features](sst_03_neural_networks.ipynb#Distributed-representations-as-features), we looked at a baseline for the ternary SST problem in which each example is modeled as the sum of its GloVe representations. A `LogisticRegression` model was used for prediction. A neural network might do better with these representations, since there might be complex relationships between the input feature dimensions that a linear classifier can't learn. \n", - "\n", - "To address this question, we want to get set up to run the experiment with a shallow neural classifier. Thus, your task is to write and submit a model wrapper function around `TorchShallowNeuralClassifier`. This function should implement hyperparameter search according to this specification:\n", - "\n", - "* Set `early_stopping=True` for all experiments.\n", - "* Using 3-fold cross-validation, exhaustively explore this set of hyperparameter combinations:\n", - " * The hidden dimensionality at 50, 100, and 200.\n", - " * The hidden activation function as `nn.Tanh()` and `nn.ReLU()`.\n", - "* For all other parameters to `TorchShallowNeuralClassifier`, use the defaults.\n", - "\n", - "\n", - "See [this notebook section](sst_02_hand_built_features.ipynb#Hyperparameter-search) for examples. You are not required to run a full evaluation with this function using `sst.experiment`, but we assume you will want to.\n", - "\n", - "We're not evaluating the quality of your model. (We've specified the protocols completely, but there will still be variation in the results.) However, the primary goal of this question is to get you thinking more about this strong baseline feature representation scheme for SST, so we're sort of hoping you feel compelled to try out variations on your own." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from torch_shallow_neural_classifier import TorchShallowNeuralClassifier\n", - "\n", - "def fit_shallow_neural_classifier_with_hyperparameter_search(X, y):\n", - " pass\n", - " ##### YOUR CODE HERE\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Sentiment shifters [2 points]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Some words have greater power than others to shift sentiment around. Because the SST has sentiment labels on all of its subconstituents, it provides an opportunity to study these shifts in detail. This question takes a first step in that direction by asking you to identify some of these sentiment shifters automatically.\n", - "\n", - "More specifically, the task is to identify words that effect a particularly large shift between the value of their sibling node and the value of their mother node. For instance, in the tree" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "tree = Tree.fromstring(\n", - " \"\"\"(1 (2 Astrology) (1 (2 is) (1 (2 not) (4 enlightening))))\"\"\")\n", - "\n", - "tree" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "we have the shifter calculations:\n", - " \n", - "* *not*: `1 - 4 = -3`\n", - "* *enlightening*: `1 - 2 = -1`\n", - "* *is*: `1 - 1 = 0`\n", - "* *Astrology*: `1 - 1 = 0`.\n", - " \n", - "__Your task__: write a function `sentiment_shifters` that accepts a `tree` argument and returns a dict mapping words to their list of shifts in `tree`. You can then run `view_top_shifters` to see the results. In addition, you can use `test_sentiment_shifters` to test your function directly. It uses the above example as the basis for the test.\n", - "\n", - "__Tips__:\n", - "\n", - "* You'll probably want to use `tree.subtrees()` to inspect all of the subtrees in each tree.\n", - "* `len(tree)` counts the number of children (immediate descendants) of `tree`.\n", - "* `isinstance(subtree[0][0], str)` will test whether the left daughter of subtree has a lexical child.\n", - "* `tree.label()` gives the label for any tree or subtree.\n", - "* Your SST reader should use `replace_root_score=False` so that you keep the root node label." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from collections import defaultdict\n", - "from operator import itemgetter\n", - "\n", - "def sentiment_shifters(tree, diffs=defaultdict(list)):\n", - " \"\"\"\n", - " Calculates the shifts in `tree`.\n", - "\n", - " Parameters\n", - " ----------\n", - " tree : nltk.tree.Tree\n", - "\n", - " diffs: defaultdict(list)\n", - " This accumulates the results for `tree`, and `view_top_shifters`\n", - " accumulates all these results into a single dict.\n", - "\n", - " Returns\n", - " -------\n", - " defaultdict mapping words to their list of shifts in `tree`.\n", - "\n", - " \"\"\"\n", - " pass\n", - " ### YOUR CODE HERE" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_sentiment_shifters(func):\n", - " \"\"\"func should be `sentiment_shifters`\"\"\"\n", - " tree = Tree.fromstring(\n", - " \"\"\"(1 (2 Astrology) (1 (2 is) (1 (2 not) (4 enlightening))))\"\"\")\n", - " expected = {\"not\": [-3], \"enlightening\": [-1], \"is\": [0], \"Astrology\": [0]}\n", - " result = func(tree)\n", - " assert result == expected, \\\n", - " (\"Error for `sentiment_shifters`: \"\n", - " \"Got\\n\\n\\t{}\\n\\nwhich differs from `expected` \"\n", - " \"in `test_sentiment_shifters`\".format(result))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "test_sentiment_shifters(sentiment_shifters)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The following utility will let you use `sentiment_shifters`. The resulting insights could inform new feature functions." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def view_top_shifters(top_n=10, mincount=100):\n", - " diffs = defaultdict(list)\n", - " for tree, label in sst.train_reader(SST_HOME) :\n", - " these_diffs = sentiment_shifters(tree, diffs=diffs)\n", - " diffs = {key: np.mean(vals) for key, vals in diffs.items()\n", - " if len(vals) >= mincount}\n", - " diffs = sorted(diffs.items(), key=itemgetter(1))\n", - " segs = ((\"Negative\", diffs[:top_n]), (\"Positive\", diffs[-top_n:]))\n", - " for label, seg in segs:\n", - " print(\"\\nTop {} {} shifters:\\n\".format(top_n, label))\n", - " for key, val in seg:\n", - " print(key, val)\n", - "\n", - "\n", - "view_top_shifters()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Your original system [3 points]\n", - "\n", - "Your task is to develop an original model for the SST ternary problem, predicting only the root-level labels. There are many options. If you spend more than a few hours on this homework problem, you should consider letting it grow into your final project! Here are some relatively manageable ideas that you might try:\n", - "\n", - "1. We didn't systematically evaluate the `bidirectional` option to the `TorchRNNClassifier`. Similarly, that model could be tweaked to allow multiple LSTM layers (at present there is only one), and you could try adding layers to the classifier portion of the model as well.\n", - "\n", - "1. We've already glimpsed the power of rich initial word representations, and later in the course we'll see that smart initialization usually leads to a performance gain in NLP, so you could perhaps achieve a winning entry with a simple model that starts in a great place.\n", - "\n", - "1. Our [practical introduction to contextual word representations](contextualreps.ipynb) covers pretrained representations and interfaces that are likely to boost the performance of any system.\n", - "\n", - "1. The `TreeNN` and `TorchTreeNN` don't perform all that well, and this could be for the same reason that RNNs don't peform well: the gradient signal doesn't propagate reliably down inside very deep trees. [Tai et al. 2015](https://www.aclweb.org/anthology/P15-1150/) sought to address this with TreeLSTMs, which are fairly easy to implement in PyTorch.\n", - "\n", - "We want to emphasize that this needs to be an __original__ system. It doesn't suffice to download code from the Web, retrain, and submit. You can build on others' code, but you have to do something new and meaningful with it.\n", - "\n", - "In the cell below, please provide a brief technical description of your original system, so that the teaching team can gain an understanding of what it does. This will help us to understand your code and analyze all the submissions to identify patterns and strategies. We also ask that you report the best score your system got during development, just to help us understand how systems performed overall." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# PLEASE MAKE SURE TO INCLUDE THE FOLLOWING BETWEEN THE START AND STOP COMMENTS:\n", - "# 1) Textual description of your system.\n", - "# 2) The code for your original system.\n", - "# 3) The score achieved by your system in place of MY_NUMBER.\n", - "# With no other changes to that line.\n", - "# You should report your score as a decimal value <=1.0\n", - "# PLEASE MAKE SURE NOT TO DELETE OR EDIT THE START AND STOP COMMENTS\n", - "\n", - "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM \n", - "# SHOULD BE ADDED BELOW THE 'IS_GRADESCOPE_ENV' CHECK CONDITION. DOING\n", - "# SO ABOVE THE CHECK MAY CAUSE THE AUTOGRADER TO FAIL.\n", - "\n", - "# START COMMENT: Enter your system description in this cell.\n", - "# My peak score was: MY_NUMBER\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - "\n", - "# STOP COMMENT: Please do not remove this comment." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Bake-off [1 point]\n", - "\n", - "As we said above, the bake-off evaluation data is the official SST test-set release. For this bake-off, you'll evaluate your original system from the above homework problem on the test set, using the ternary class problem. Rules:\n", - "\n", - "1. Only one evaluation is permitted.\n", - "1. No additional system tuning is permitted once the bake-off has started.\n", - "\n", - "The cells below this one constitute your bake-off entry.\n", - "\n", - "Systems that enter will receive the additional homework point, and systems that achieve the top score will receive an additional 0.5 points. We will test the top-performing systems ourselves, and only systems for which we can reproduce the reported results will win the extra 0.5 points.\n", - "\n", - "Late entries will be accepted, but they cannot earn the extra 0.5 points. Similarly, you cannot win the bake-off unless your homework is submitted on time.\n", - "\n", - "The announcement will include the details on where to submit your entry." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Enter your bake-off assessment code in this cell.\n", - "# Place your code in the scope of the 'IS_GRADESCOPE_ENV'\n", - "# conditional.\n", - "# Please do not remove this comment.\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - " # Please enter your code in the scope of the above conditional.\n", - " ##### YOUR CODE HERE\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# On an otherwise blank line in this cell, please enter\n", - "# your macro-average F1 value as reported by the code above.\n", - "# Please enter only a number between 0 and 1 inclusive.\n", - "# Please do not remove this comment.\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - " # Please enter your score in the scope of the above conditional.\n", - " ##### YOUR CODE HERE\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.7" - }, - "widgets": { - "state": {}, - "version": "1.1.2" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/hw_wordentail.ipynb b/hw_wordentail.ipynb index 383ce47..d723c36 100644 --- a/hw_wordentail.ipynb +++ b/hw_wordentail.ipynb @@ -640,7 +640,7 @@ "# You should report your score as a decimal value <=1.0\n", "# PLEASE MAKE SURE NOT TO DELETE OR EDIT THE START AND STOP COMMENTS\n", "\n", - "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM \n", + "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM\n", "# SHOULD BE ADDED BELOW THE 'IS_GRADESCOPE_ENV' CHECK CONDITION. DOING\n", "# SO ABOVE THE CHECK MAY CAUSE THE AUTOGRADER TO FAIL.\n", "\n", @@ -718,9 +718,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.7" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 1 + "nbformat_minor": 4 } diff --git a/hw_wordrelatedness.ipynb b/hw_wordrelatedness.ipynb new file mode 100644 index 0000000..03a1039 --- /dev/null +++ b/hw_wordrelatedness.ipynb @@ -0,0 +1,1491 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Homework and bake-off: Word relatedness" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "__author__ = \"Christopher Potts\"\n", + "__version__ = \"CS224u, Stanford, Spring 2021\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Contents\n", + "\n", + "1. [Overview](#Overview)\n", + "1. [Set-up](#Set-up)\n", + "1. [Development dataset](#Development-dataset)\n", + " 1. [Vocabulary](#Vocabulary)\n", + " 1. [Score distribution](#Score-distribution)\n", + " 1. [Repeated pairs](#Repeated-pairs)\n", + "1. [Evaluation](#Evaluation)\n", + "1. [Error analysis](#Error-analysis)\n", + "1. [Homework questions](#Homework-questions)\n", + " 1. [PPMI as a baseline [0.5 points]](#PPMI-as-a-baseline-[0.5-points])\n", + " 1. [Gigaword with LSA at different dimensions [0.5 points]](#Gigaword-with-LSA-at-different-dimensions-[0.5-points])\n", + " 1. [t-test reweighting [2 points]](#t-test-reweighting-[2-points])\n", + " 1. [Pooled BERT representations [1 point]](#Pooled-BERT-representations-[1-point])\n", + " 1. [Learned distance functions [2 points]](#Learned-distance-functions-[2-points])\n", + " 1. [Your original system [3 points]](#Your-original-system-[3-points])\n", + "1. [Bake-off [1 point]](#Bake-off-[1-point])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Overview\n", + "\n", + "Word similarity and relatedness datasets have long been used to evaluate distributed representations. This notebook provides code for conducting such analyses with a new word relatedness datasets. It consists of word pairs, each with an associated human-annotated relatedness score. \n", + "\n", + "The evaluation metric for each dataset is the [Spearman correlation coefficient $\\rho$](https://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient) between the annotated scores and your distances, as is standard in the literature. Since the train and test datasets contain both similarity and relatedness datasets, we will also report separate scores for each of these sub-tasks as well as an overall score.\n", + "\n", + "This homework ([questions at the bottom of this notebook](#Homework-questions)) asks you to write code that uses the count matrices in `data/vsmdata` to create and evaluate some baseline models. The final question asks you to create your own original system for this task, using any data you wish. This accounts for 9 of the 10 points for this assignment.\n", + "\n", + "For the associated bake-off, we will distribute a new dataset, and you will evaluate your original system (no additional training or tuning allowed!) on that datasets and submit your predictions. Systems that enter will receive the additional homework point, and systems that achieve the top score will receive an additional 0.5 points." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set-up" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from collections import defaultdict\n", + "import csv\n", + "import itertools\n", + "import numpy as np\n", + "import os\n", + "import pandas as pd\n", + "import random\n", + "from scipy.stats import spearmanr\n", + "\n", + "import vsm\n", + "import utils" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "utils.fix_random_seeds()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "VSM_HOME = os.path.join('data', 'vsmdata')\n", + "\n", + "DATA_HOME = os.path.join('data', 'wordrelatedness')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Development dataset" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can use development dataset freely, since our bake-off evalutions involve a new test set." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "dev_df = pd.read_csv(\n", + " os.path.join(DATA_HOME, \"cs224u-wordrelatedness-dev.csv\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The dataset consists of word pairs with scores:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
word1word2score
0abandonbutton0.180000
1abandoncrane0.160000
2abandonditch0.011434
3abandonfrost0.180000
4abandonrailroad0.360000
\n", + "
" + ], + "text/plain": [ + " word1 word2 score\n", + "0 abandon button 0.180000\n", + "1 abandon crane 0.160000\n", + "2 abandon ditch 0.011434\n", + "3 abandon frost 0.180000\n", + "4 abandon railroad 0.360000" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dev_df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This gives the number of word pairs in the data:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "5012" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dev_df.shape[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The test set will contain 1500 word pairs with scores of the same type. No word pair in the development set appears in the test set, but some of the individual words are repeated in the test set." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Vocabulary" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The full vocabulary in the dataframe can be extracted as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "dev_vocab = set(dev_df.word1.values) | set(dev_df.word2.values)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2805" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(dev_vocab)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The vocabulary for the bake-off test i different – it is partly overlapping with the above. If you want to be sure ahead of time that your system has a representation for every word in the dev and test sets, then you can check against the vocabularies of any of the VSMs in `data/vsmdata` (which all have the same vocabulary). For example:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "task_index = pd.read_csv(\n", + " os.path.join(VSM_HOME, 'yelp_window5-scaled.csv.gz'),\n", + " usecols=[0], index_col=0)\n", + "\n", + "full_task_vocab = list(task_index.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "6000" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(full_task_vocab)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you can process every one of those words, then you are all set. Alternatively, you can wait to see the test set and make system adjustments to ensure that you can process all those words. This is fine as long as you are not tuning your predictions." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Score distribution" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "All the scores fall in $[0, 1]$, and the dataset skews towards words with low scores, meaning low relatedness:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "ax = dev_df.plot.hist().set_xlabel(\"Relatedness score\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Repeated pairs" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The development data has some word pairs with multiple distinct scores in it. Here we create a `pd.Series` that contains these word pairs:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "repeats = dev_df.groupby(['word1', 'word2']).apply(lambda x: x.score.var())\n", + "\n", + "repeats = repeats[repeats > 0].sort_values(ascending=False)\n", + "\n", + "repeats.name = 'score variance'" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "281" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "repeats.shape[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `pd.Series` is sorted with the highest variance items at the top:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "word1 word2 \n", + "tiger tiger 0.496377\n", + "female woman 0.483799\n", + "cat feline 0.448513\n", + "buck dollar 0.422516\n", + "midday noon 0.419930\n", + "Name: score variance, dtype: float64" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "repeats.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Since this is development data, it is up to you how you want to handle these repeats. The test set has no repeated pairs in it." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our evaluation function is `vsm.word_relatedness_evaluation`. Its arguments:\n", + " \n", + "1. A relatedness dataset `pd.DataFrame` – e.g., `dev_df` as given above.\n", + "1. A VSM `pd.DataFrame` – e.g., `giga5` or some transformation thereof, or a GloVe embedding space, or something you have created on your own. The function checks that you can supply a representation for ever word in `dev_df` and raises an exception if you can't.\n", + "1. Optionally a `distfunc` argument, which defaults to `vsm.cosine`.\n", + "\n", + "The function returns a tuple:\n", + "\n", + "1. A copy of `dev_df` with a new column giving your predictions.\n", + "1. The Spearman $\\rho$ value (our primary score).\n", + "\n", + "Important note: Internally, `vsm.word_relatedness_evaluation` uses `-distfunc(x1, x2)` as its score, where `x1` and `x2` are vector representations of words. This is because the scores in our data are _positive_ relatedness scores, whereas we are assuming that `distfunc` is a _distance_ function.\n", + "\n", + "Here's a simple illustration using one of our count matrices:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "count_df = pd.read_csv(\n", + " os.path.join(VSM_HOME, \"giga_window5-scaled.csv.gz\"), index_col=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "count_pred_df, count_rho = vsm.word_relatedness_evaluation(dev_df, count_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.08023032812449556" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "count_rho" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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word1word2scoreprediction
0abandonbutton0.180000-0.336291
1abandoncrane0.160000-0.307229
2abandonditch0.011434-0.211550
3abandonfrost0.180000-0.442436
4abandonrailroad0.360000-0.363288
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" + ], + "text/plain": [ + " word1 word2 score prediction\n", + "0 abandon button 0.180000 -0.336291\n", + "1 abandon crane 0.160000 -0.307229\n", + "2 abandon ditch 0.011434 -0.211550\n", + "3 abandon frost 0.180000 -0.442436\n", + "4 abandon railroad 0.360000 -0.363288" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "count_pred_df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It's instructive to compare this against a truly random system, which we can create by simply having a custom distance function that returns a random number in [0, 1] for each example, making no use of the VSM itself:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "def random_scorer(x1, x2):\n", + " \"\"\"`x1` and `x2` are vectors, to conform to the requirements\n", + " of `vsm.word_relatedness_evaluation`, but this function just\n", + " returns a random number in [0, 1].\"\"\"\n", + " return random.random()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.008404428343748976" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "random_pred_df, random_rho = vsm.word_relatedness_evaluation(\n", + " dev_df, count_df, distfunc=random_scorer)\n", + "\n", + "random_rho" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This is a truly baseline system!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Error analysis\n", + "\n", + "For error analysis, we can look at the words with the largest delta between the gold score and the distance value in our VSM. We do these comparisons based on ranks, just as with our primary metric (Spearman $\\rho$), and we normalize both rankings so that they have a comparable number of levels." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "def error_analysis(pred_df):\n", + " pred_df = pred_df.copy()\n", + " pred_df['relatedness_rank'] = _normalized_ranking(pred_df.prediction)\n", + " pred_df['score_rank'] = _normalized_ranking(pred_df.score)\n", + " pred_df['error'] = abs(pred_df['relatedness_rank'] - pred_df['score_rank'])\n", + " return pred_df.sort_values('error')\n", + "\n", + "\n", + "def _normalized_ranking(series):\n", + " ranks = series.rank(method='dense')\n", + " return ranks / ranks.sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Best predictions:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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word1word2scorepredictionrelatedness_rankscore_rankerror
892bootcliff0.260000-0.2043310.0001590.0001593.272272e-08
3148governorinterview0.001724-0.5670410.0000050.0000051.141903e-07
1740conclusionsounding0.009619-0.3548910.0000470.0000461.277154e-07
3121glassroad0.340000-0.1821070.0001840.0001841.418967e-07
995brickceiling0.560000-0.1325960.0002610.0002612.190320e-07
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" + ], + "text/plain": [ + " word1 word2 score prediction relatedness_rank \\\n", + "892 boot cliff 0.260000 -0.204331 0.000159 \n", + "3148 governor interview 0.001724 -0.567041 0.000005 \n", + "1740 conclusion sounding 0.009619 -0.354891 0.000047 \n", + "3121 glass road 0.340000 -0.182107 0.000184 \n", + "995 brick ceiling 0.560000 -0.132596 0.000261 \n", + "\n", + " score_rank error \n", + "892 0.000159 3.272272e-08 \n", + "3148 0.000005 1.141903e-07 \n", + "1740 0.000046 1.277154e-07 \n", + "3121 0.000184 1.418967e-07 \n", + "995 0.000261 2.190320e-07 " + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "error_analysis(count_pred_df).head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Worst predictions:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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word1word2scorepredictionrelatedness_rankscore_rankerror
3208growsprouting0.950-0.5183919.015989e-060.0004220.000413
3207growsprouting0.950-0.5183919.015989e-060.0004220.000413
4595repeatingreplicate0.925-0.7280524.507995e-070.0004170.000417
4596repeatingreplicate0.925-0.7280524.507995e-070.0004170.000417
4337photophotography0.940-0.6832721.262239e-060.0004200.000418
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" + ], + "text/plain": [ + " word1 word2 score prediction relatedness_rank score_rank \\\n", + "3208 grow sprouting 0.950 -0.518391 9.015989e-06 0.000422 \n", + "3207 grow sprouting 0.950 -0.518391 9.015989e-06 0.000422 \n", + "4595 repeating replicate 0.925 -0.728052 4.507995e-07 0.000417 \n", + "4596 repeating replicate 0.925 -0.728052 4.507995e-07 0.000417 \n", + "4337 photo photography 0.940 -0.683272 1.262239e-06 0.000420 \n", + "\n", + " error \n", + "3208 0.000413 \n", + "3207 0.000413 \n", + "4595 0.000417 \n", + "4596 0.000417 \n", + "4337 0.000418 " + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "error_analysis(count_pred_df).tail()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Homework questions\n", + "\n", + "Please embed your homework responses in this notebook, and do not delete any cells from the notebook. (You are free to add as many cells as you like as part of your responses.)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### PPMI as a baseline [0.5 points]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The insight behind PPMI is a recurring theme in word representation learning, so it is a natural baseline for our task. This question asks you to write code for conducting such experiments.\n", + "\n", + "Your task: write a function called `run_giga_ppmi_baseline` that does the following:\n", + "\n", + "1. Reads the Gigaword count matrix with a window of 20 and a flat scaling function into a `pd.DataFrame`, as is done in the VSM notebooks. The file is `data/vsmdata/giga_window20-flat.csv.gz`, and the VSM notebooks provide examples of the needed code.\n", + "1. Reweights this count matrix with PPMI.\n", + "1. Evaluates this reweighted matrix using `vsm.word_relatedness_evaluation` on `dev_df` as defined above, with `distfunc` set to the default of `vsm.cosine`.\n", + "1. Returns the return value of this call to `vsm.word_relatedness_evaluation`.\n", + "\n", + "The goal of this question is to help you get more familiar with the code in `vsm` and the function `vsm.word_relatedness_evaluation`.\n", + "\n", + "The function `test_run_giga_ppmi_baseline` can be used to test that you've implemented this specification correctly." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "def run_giga_ppmi_baseline():\n", + " pass\n", + " ##### YOUR CODE HERE\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "def test_run_giga_ppmi_baseline(func):\n", + " \"\"\"`func` should be `run_giga_ppmi_baseline\"\"\"\n", + " pred_df, rho = func()\n", + " rho = round(rho, 3)\n", + " expected = 0.351\n", + " assert rho == expected, \\\n", + " \"Expected rho of {}; got {}\".format(expected, rho)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_run_giga_ppmi_baseline(run_giga_ppmi_baseline)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Gigaword with LSA at different dimensions [0.5 points]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We might expect PPMI and LSA to form a solid pipeline that combines the strengths of PPMI with those of dimensionality reduction. However, LSA has a hyper-parameter $k$ – the dimensionality of the final representations – that will impact performance. This problem asks you to create code that will help you explore this approach.\n", + "\n", + "Your task: write a wrapper function `run_ppmi_lsa_pipeline` that does the following:\n", + "\n", + "1. Takes as input a count `pd.DataFrame` and an LSA parameter `k`.\n", + "1. Reweights the count matrix with PPMI.\n", + "1. Applies LSA with dimensionality `k`.\n", + "1. Evaluates this reweighted matrix using `vsm.word_relatedness_evaluation` with `dev_df` as defined above. The return value of `run_ppmi_lsa_pipeline` should be the return value of this call to `vsm.word_relatedness_evaluation`.\n", + "\n", + "The goal of this question is to help you get a feel for how LSA can contribute to this problem. \n", + "\n", + "The function `test_run_ppmi_lsa_pipeline` will test your function on the count matrix in `data/vsmdata/giga_window20-flat.csv.gz`." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "def run_ppmi_lsa_pipeline(count_df, k):\n", + " pass\n", + " ##### YOUR CODE HERE\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "def test_run_ppmi_lsa_pipeline(func):\n", + " \"\"\"`func` should be `run_ppmi_lsa_pipeline`\"\"\"\n", + " giga20 = pd.read_csv(\n", + " os.path.join(VSM_HOME, \"giga_window20-flat.csv.gz\"), index_col=0)\n", + " pred_df, rho = func(giga20, k=10)\n", + " rho = round(rho, 3)\n", + " expected = 0.319\n", + " assert rho == expected,\\\n", + " \"Expected rho of {}; got {}\".format(expected, rho)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_run_ppmi_lsa_pipeline(run_ppmi_lsa_pipeline)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### t-test reweighting [2 points]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The t-test statistic can be thought of as a reweighting scheme. For a count matrix $X$, row index $i$, and column index $j$:\n", + "\n", + "$$\\textbf{ttest}(X, i, j) = \n", + "\\frac{\n", + " P(X, i, j) - \\big(P(X, i, *)P(X, *, j)\\big)\n", + "}{\n", + "\\sqrt{(P(X, i, *)P(X, *, j))}\n", + "}$$\n", + "\n", + "where $P(X, i, j)$ is $X_{ij}$ divided by the total values in $X$, $P(X, i, *)$ is the sum of the values in row $i$ of $X$ divided by the total values in $X$, and $P(X, *, j)$ is the sum of the values in column $j$ of $X$ divided by the total values in $X$.\n", + "\n", + "Your task: implement this reweighting scheme. You can use `test_ttest_implementation` below to check that your implementation is correct. You do not need to use this for any evaluations, though we hope you will be curious enough to do so!" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "def ttest(df):\n", + " pass\n", + " ##### YOUR CODE HERE\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "def test_ttest_implementation(func):\n", + " \"\"\"`func` should be `ttest`\"\"\"\n", + " X = pd.DataFrame([\n", + " [1., 4., 3., 0.],\n", + " [2., 43., 7., 12.],\n", + " [5., 6., 19., 0.],\n", + " [1., 11., 1., 4.]])\n", + " actual = np.array([\n", + " [ 0.04655, -0.01337, 0.06346, -0.09507],\n", + " [-0.11835, 0.13406, -0.20846, 0.10609],\n", + " [ 0.16621, -0.23129, 0.38123, -0.18411],\n", + " [-0.0231 , 0.0563 , -0.14549, 0.10394]])\n", + " predicted = func(X)\n", + " assert np.array_equal(predicted.round(5), actual), \\\n", + " \"Your ttest result is\\n{}\".format(predicted.round(5))" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_ttest_implementation(ttest)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Pooled BERT representations [1 point]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The notebook [vsm_04_contextualreps.ipynb](vsm_04_contextualreps.ipynb) explores methods for deriving static vector representations of words from the contextual representations given by models like BERT and RoBERTa. The methods are due to [Bommasani et al. 2020](https://www.aclweb.org/anthology/2020.acl-main.431). The simplest of these methods involves processing the words as independent texts and pooling the sub-word representations that result, using a function like mean or max.\n", + "\n", + "Your task: write a function `evaluate_pooled_bert` that will enable exploration of this approach. The function should do the following:\n", + "\n", + "1. Take as its arguments (a) a word relatedness `pd.DataFrame` `rel_df` (e.g., `dev_df`), (b) a `layer` index (see below), and (c) a `pool_func` value (see below).\n", + "1. Set up a BERT tokenizer and BERT model based on `'bert-base-uncased'`.\n", + "1. Use `vsm.create_subword_pooling_vsm` to create a VSM (a `pd.DataFrame`) with the user's values for `layer` and `pool_func`.\n", + "1. Return the return value of `vsm.word_relatedness_evaluation` using this new VSM, evaluated on `rel_df` with `distfunc` set to its default value.\n", + "\n", + "The function `vsm.create_subword_pooling_vsm` does the heavy-lifting. Your task is really just to put these pieces together. The result will be the start of a flexible framework for seeing how these methods do on our task. \n", + "\n", + "The function `test_evaluate_pooled_bert` can help you obtain the design we are seeking." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "from transformers import BertModel, BertTokenizer\n", + "\n", + "def evaluate_pooled_bert(rel_df, layer, pool_func):\n", + " bert_weights_name = 'bert-base-uncased'\n", + "\n", + " # Initialize a BERT tokenizer and BERT model based on\n", + " # `bert_weights_name`:\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Get the vocabulary from `rel_df`:\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Use `vsm.create_subword_pooling_vsm` with the user's arguments:\n", + " ##### YOUR CODE HERE\n", + "\n", + " # Return the results of the relatedness evalution:\n", + " ##### YOUR CODE HERE\n" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "def test_evaluate_pooled_bert(func):\n", + " import torch\n", + " rel_df = pd.DataFrame([\n", + " {'word1': 'porcupine', 'word2': 'capybara', 'score': 0.6},\n", + " {'word1': 'antelope', 'word2': 'springbok', 'score': 0.5},\n", + " {'word1': 'llama', 'word2': 'camel', 'score': 0.4},\n", + " {'word1': 'movie', 'word2': 'play', 'score': 0.3}])\n", + " layer = 2\n", + " pool_func = vsm.max_pooling\n", + " pred_df, rho = evaluate_pooled_bert(rel_df, layer, pool_func)\n", + " rho = round(rho, 2)\n", + " expected_rho = 0.40\n", + " assert rho == expected_rho, \\\n", + " \"Expected rho={}; got rho={}\".format(expected_rho, rho)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_evaluate_pooled_bert(evaluate_pooled_bert)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learned distance functions [2 points]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The presentation thus far leads one to assume that the `distfunc` argument used in the experiments will be a standard vector distance function like `vsm.cosine` or `vsm.euclidean`. However, the framework itself simply requires that this function map two fixed-dimensional vectors to a real number. This opens up a world of possibilities. This question asks you to dip a toe in these waters.\n", + "\n", + "Your task: write a function `run_knn_score_model` for models in this class. The function should:\n", + "\n", + "1. Take as its arguments (a) a VSM dataframe `vsm_df`, (b) a relatedness dataset (e.g., `dev_df`), and (c) a `test_size` value between 0.0 and 1.0 that can be passed directly to `train_test_split` (see below).\n", + "1. Create a feature matrix `X`: each word pair in `dev_df` should be represented by the concatenation of the vectors for word1 and word2 from `vsm_df`.\n", + "1. Create a score vector `y`, which is just the `score` column in `dev_df`.\n", + "1. Split the dataset `(X, y)` into train and test portions using [sklearn.model_selection.train_test_split](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html).\n", + "1. Train an [sklearn.neighbors.KNeighborsRegressor](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html#sklearn.neighbors.KNeighborsRegressor) model on the train split from step 4, with default hyperparameters.\n", + "1. Return the value of the `score` method of the trained `KNeighborsRegressor` model on the test split from step 4.\n", + "\n", + "The functions `test_knn_feature_matrix` and `knn_represent` will help you test the crucial representational aspects of this.\n", + "\n", + "Note: if you decide to apply this approach to our task as part of an original system, recall that `vsm.create_subword_pooling_vsm` returns `-d` where `d` is the value computed by `distfunc`, since it assumes that `distfunc` is a distance value of some kind rather than a relatedness/similarity value. Since most regression models will return positive scores for positive associations, you will probably want to undue this by having your `distfunc` return the negative of its value." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn.neighbors import KNeighborsRegressor\n", + "\n", + "def run_knn_score_model(vsm_df, dev_df, test_size=0.20):\n", + " pass\n", + "\n", + " # Complete `knn_feature_matrix` for this step.\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Get the values of the 'score' column in `dev_df`\n", + " # and store them in a list or array `y`.\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Use `train_test_split` to split (X, y) into train and\n", + " # test protions, with `test_size` as the test size.\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Instantiate a `KNeighborsRegressor` with default arguments:\n", + " ##### YOUR CODE HERE\n", + "\n", + " # Fit the model on the training data:\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + " # Return the value of `score` for your model on the test split\n", + " # you created above:\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + "def knn_feature_matrix(vsm_df, rel_df):\n", + " pass\n", + " # Complete `knn_represent` and use it to create a feature\n", + " # matrix `np.array`:\n", + " ##### YOUR CODE HERE\n", + "\n", + "\n", + "def knn_represent(word1, word2, vsm_df):\n", + " pass\n", + " # Use `vsm_df` to get vectors for `word1` and `word2`\n", + " # and concatenate them into a single vector:\n", + " ##### YOUR CODE HERE\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "def test_knn_feature_matrix(func):\n", + " rel_df = pd.DataFrame([\n", + " {'word1': 'w1', 'word2': 'w2', 'score': 0.1},\n", + " {'word1': 'w1', 'word2': 'w3', 'score': 0.2}])\n", + " vsm_df = pd.DataFrame([\n", + " [1, 2, 3.],\n", + " [4, 5, 6.],\n", + " [7, 8, 9.]], index=['w1', 'w2', 'w3'])\n", + " expected = np.array([\n", + " [1, 2, 3, 4, 5, 6.],\n", + " [1, 2, 3, 7, 8, 9.]])\n", + " result = func(vsm_df, rel_df)\n", + " assert np.array_equal(result, expected), \\\n", + " \"Your `knn_feature_matrix` returns: {}\\nWe expect: {}\".format(\n", + " result, expected)\n", + "\n", + "def test_knn_represent(func):\n", + " vsm_df = pd.DataFrame([\n", + " [1, 2, 3.],\n", + " [4, 5, 6.],\n", + " [7, 8, 9.]], index=['w1', 'w2', 'w3'])\n", + " result = func('w1', 'w3', vsm_df)\n", + " expected = np.array([1, 2, 3, 7, 8, 9.])\n", + " assert np.array_equal(result, expected), \\\n", + " \"Your `knn_represent` returns: {}\\nWe expect: {}\".format(\n", + " result, expected)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " test_knn_represent(knn_represent)\n", + " test_knn_feature_matrix(knn_feature_matrix)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Your original system [3 points]\n", + "\n", + "This question asks you to design your own model. You can of course include steps made above (ideally, the above questions informed your system design!), but your model should not be literally identical to any of the above models. Other ideas: retrofitting, autoencoders, GloVe, subword modeling, ... \n", + "\n", + "Requirements:\n", + "\n", + "1. Your system must work with `vsm.word_relatedness_evaluation`. You are free to specify the VSM and the value of `distfunc`.\n", + "\n", + "1. Your code must be self-contained, so that we can work with your model directly in your homework submission notebook. If your model depends on external data or other resources, please submit a ZIP archive containing these resources along with your submission.\n", + "\n", + "In the cell below, please provide a brief technical description of your original system, so that the teaching team can gain an understanding of what it does. This will help us to understand your code and analyze all the submissions to identify patterns and strategies. We also ask that you report the best score your system got during development, just to help us understand how systems performed overall." + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "# PLEASE MAKE SURE TO INCLUDE THE FOLLOWING BETWEEN THE START AND STOP COMMENTS:\n", + "# 1) Textual description of your system.\n", + "# 2) The code for your original system.\n", + "# 3) The score achieved by your system in place of MY_NUMBER.\n", + "# With no other changes to that line.\n", + "# You should report your score as a decimal value <=1.0\n", + "# PLEASE MAKE SURE NOT TO DELETE OR EDIT THE START AND STOP COMMENTS\n", + "\n", + "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM\n", + "# SHOULD BE ADDED BELOW THE 'IS_GRADESCOPE_ENV' CHECK CONDITION. DOING\n", + "# SO ABOVE THE CHECK MAY CAUSE THE AUTOGRADER TO FAIL.\n", + "\n", + "# START COMMENT: Enter your system description in this cell.\n", + "# My peak score was: MY_NUMBER\n", + "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", + " pass\n", + "\n", + "# STOP COMMENT: Please do not remove this comment." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bake-off [1 point]\n", + "\n", + "For the bake-off, you simply need to evaluate your original system on the file \n", + "\n", + "`vsmdata/cs224u-wordrelatedness-bakeoff-test-unlabeled.csv`\n", + "\n", + "This contains only word pairs (no scores), so `vsm.word_relatedness_evaluation` will simply make predictions without doing any scoring. Use that function to make predictions with your original system, store the resulting `pred_df` to a file, and then upload the file as your bake-off submission.\n", + "\n", + "The following function should be used to conduct this evaluation:" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "def create_bakeoff_submission(\n", + " vsm_df,\n", + " distfunc,\n", + " output_filename=\"cs224u-wordrelatedness-bakeoff-entry.csv\"):\n", + "\n", + " test_df = pd.read_csv(\n", + " os.path.join(DATA_HOME, \"cs224u-wordrelatedness-test-unlabeled.csv\"))\n", + "\n", + " pred_df, _ = vsm.word_relatedness_evaluation(test_df, vsm_df, distfunc=distfunc)\n", + "\n", + " pred_df.to_csv(output_filename)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For example, if `count_df` were the VSM for my system, and I wanted my distance function to be `vsm.euclidean`, I would do" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "create_bakeoff_submission(count_df, vsm.euclidean)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This creates a file `cs224u-wordrelatedness-bakeoff-entry.csv` in the current directory. That file should be uploaded as-is. Please do not change its name.\n", + "\n", + "Only one upload per team is permitted, and you should do no tuning of your system based on what you see in `pred_df` – you should not study that file in anyway, beyond perhaps checking that it contains what you expected it to contain. The upload function will do some additional checking to ensure that your file is well-formed.\n", + "\n", + "People who enter will receive the additional homework point, and people whose systems achieve the top score will receive an additional 0.5 points. We will test the top-performing systems ourselves, and only systems for which we can reproduce the reported results will win the extra 0.5 points.\n", + "\n", + "Late entries will be accepted, but they cannot earn the extra 0.5 points." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + }, + "widgets": { + "state": {}, + "version": "1.1.2" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/hw_wordsim.ipynb b/hw_wordsim.ipynb deleted file mode 100644 index 33469ae..0000000 --- a/hw_wordsim.ipynb +++ /dev/null @@ -1,1186 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Homework and bake-off: Word similarity" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Contents\n", - "\n", - "1. [Overview](#Overview)\n", - "1. [Set-up](#Set-up)\n", - "1. [Dataset readers](#Dataset-readers)\n", - "1. [Dataset comparisons](#Dataset-comparisons)\n", - " 1. [Vocab overlap](#Vocab-overlap)\n", - " 1. [Pair overlap and score correlations](#Pair-overlap-and-score-correlations)\n", - "1. [Evaluation](#Evaluation)\n", - " 1. [Dataset evaluation](#Dataset-evaluation)\n", - " 1. [Dataset error analysis](#Dataset-error-analysis)\n", - " 1. [Full evaluation](#Full-evaluation)\n", - "1. [Homework questions](#Homework-questions)\n", - " 1. [PPMI as a baseline [0.5 points]](#PPMI-as-a-baseline-[0.5-points])\n", - " 1. [Gigaword with LSA at different dimensions [0.5 points]](#Gigaword-with-LSA-at-different-dimensions-[0.5-points])\n", - " 1. [Gigaword with GloVe [0.5 points]](#Gigaword-with-GloVe-[0.5-points])\n", - " 1. [Dice coefficient [0.5 points]](#Dice-coefficient-[0.5-points])\n", - " 1. [t-test reweighting [2 points]](#t-test-reweighting-[2-points])\n", - " 1. [Enriching a VSM with subword information [2 points]](#Enriching-a-VSM-with-subword-information-[2-points])\n", - " 1. [Your original system [3 points]](#Your-original-system-[3-points])\n", - "1. [Bake-off [1 point]](#Bake-off-[1-point])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Overview\n", - "\n", - "Word similarity datasets have long been used to evaluate distributed representations. This notebook provides basic code for conducting such analyses with a number of datasets:\n", - "\n", - "| Dataset | Pairs | Task-type | Current best Spearman $\\rho$ | Best $\\rho$ paper | |\n", - "|---------|-------|-----------|------------------------------|-------------------|---|\n", - "| [WordSim-353](http://www.gabrilovich.com/resources/data/wordsim353/) | 353 | Relatedness | 82.8 | [Speer et al. 2017](https://arxiv.org/abs/1612.03975) |\n", - "| [MTurk-771](http://www2.mta.ac.il/~gideon/mturk771.html) | 771 | Relatedness | 81.0 | [Speer et al. 2017](https://arxiv.org/abs/1612.03975) |\n", - "| [The MEN Test Collection](https://staff.fnwi.uva.nl/e.bruni/MEN) | 3,000 | Relatedness | 86.6 | [Speer et al. 2017](https://arxiv.org/abs/1612.03975) | \n", - "| [SimVerb-3500-dev](https://www.aclweb.org/anthology/D16-1235/) | 500 | Similarity | 61.1 | [Mrkišć et al. 2016](https://arxiv.org/pdf/1603.00892.pdf) |\n", - "| [SimVerb-3500-test](https://www.aclweb.org/anthology/D16-1235/) | 3,000 | Similarity | 62.4 | [Mrkišć et al. 2016](https://arxiv.org/pdf/1603.00892.pdf) |\n", - "\n", - "Each of the similarity datasets contains word pairs with an associated human-annotated similarity score. (We convert these to distances to align intuitively with our distance measure functions.) The evaluation code measures the distance between the word pairs in your chosen VSM (which should be a `pd.DataFrame`).\n", - "\n", - "The evaluation metric for each dataset is the [Spearman correlation coefficient $\\rho$](https://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient) between the annotated scores and your distances, as is standard in the literature. We also macro-average these correlations across the datasets for an overall summary. (In using the macro-average, we are saying that we care about all the datasets equally, even though they vary in size.)\n", - "\n", - "This homework ([questions at the bottom of this notebook](#Homework-questions)) asks you to write code that uses the count matrices in `data/vsmdata` to create and evaluate some baseline models as well as an original model $M$ that you design. This accounts for 9 of the 10 points for this assignment.\n", - "\n", - "For the associated bake-off, we will distribute two new word similarity or relatedness datasets and associated reader code, and you will evaluate $M$ (no additional training or tuning allowed!) on those new datasets. Systems that enter will receive the additional homework point, and systems that achieve the top score will receive an additional 0.5 points." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Set-up" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from collections import defaultdict\n", - "import csv\n", - "import itertools\n", - "import numpy as np\n", - "import os\n", - "import pandas as pd\n", - "from scipy.stats import spearmanr\n", - "import vsm\n", - "from IPython.display import display" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "VSM_HOME = os.path.join('data', 'vsmdata')\n", - "\n", - "WORDSIM_HOME = os.path.join('data', 'wordsim')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Dataset readers" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def wordsim_dataset_reader(\n", - " src_filename,\n", - " header=False,\n", - " delimiter=',',\n", - " score_col_index=2):\n", - " \"\"\"\n", - " Basic reader that works for all similarity datasets. They are\n", - " all tabular-style releases where the first two columns give the\n", - " word and a later column (`score_col_index`) gives the score.\n", - "\n", - " Parameters\n", - " ----------\n", - " src_filename : str\n", - " Full path to the source file.\n", - "\n", - " header : bool\n", - " Whether `src_filename` has a header.\n", - "\n", - " delimiter : str\n", - " Field delimiter in `src_filename`.\n", - "\n", - " score_col_index : int\n", - " Column containing the similarity scores Default: 2\n", - "\n", - " Yields\n", - " ------\n", - " (str, str, float)\n", - " (w1, w2, score) where `score` is the negative of the similarity\n", - " score in the file so that we are intuitively aligned with our\n", - " distance-based code. To align with our VSMs, all the words are\n", - " downcased.\n", - "\n", - " \"\"\"\n", - " with open(src_filename) as f:\n", - " reader = csv.reader(f, delimiter=delimiter)\n", - " if header:\n", - " next(reader)\n", - " for row in reader:\n", - " w1 = row[0].strip().lower()\n", - " w2 = row[1].strip().lower()\n", - " score = row[score_col_index]\n", - " # Negative of scores to align intuitively with distance functions:\n", - " score = -float(score)\n", - " yield (w1, w2, score)\n", - "\n", - "def wordsim353_reader():\n", - " \"\"\"WordSim-353: http://www.gabrilovich.com/resources/data/wordsim353/\"\"\"\n", - " src_filename = os.path.join(\n", - " WORDSIM_HOME, 'wordsim353', 'combined.csv')\n", - " return wordsim_dataset_reader(\n", - " src_filename, header=True)\n", - "\n", - "def mturk771_reader():\n", - " \"\"\"MTURK-771: http://www2.mta.ac.il/~gideon/mturk771.html\"\"\"\n", - " src_filename = os.path.join(\n", - " WORDSIM_HOME, 'MTURK-771.csv')\n", - " return wordsim_dataset_reader(\n", - " src_filename, header=False)\n", - "\n", - "def simverb3500dev_reader():\n", - " \"\"\"SimVerb-3500: https://www.aclweb.org/anthology/D16-1235/\"\"\"\n", - " src_filename = os.path.join(\n", - " WORDSIM_HOME, 'SimVerb-3500', 'SimVerb-500-dev.txt')\n", - " return wordsim_dataset_reader(\n", - " src_filename, delimiter=\"\\t\", header=False, score_col_index=3)\n", - "\n", - "def simverb3500test_reader():\n", - " \"\"\"SimVerb-3500: https://www.aclweb.org/anthology/D16-1235/\"\"\"\n", - " src_filename = os.path.join(\n", - " WORDSIM_HOME, 'SimVerb-3500', 'SimVerb-3000-test.txt')\n", - " return wordsim_dataset_reader(\n", - " src_filename, delimiter=\"\\t\", header=False, score_col_index=3)\n", - "\n", - "def men_reader():\n", - " \"\"\"MEN: https://staff.fnwi.uva.nl/e.bruni/MEN\"\"\"\n", - " src_filename = os.path.join(\n", - " WORDSIM_HOME, 'MEN', 'MEN_dataset_natural_form_full')\n", - " return wordsim_dataset_reader(\n", - " src_filename, header=False, delimiter=' ')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This collection of readers will be useful for flexible evaluations:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "READERS = (wordsim353_reader, mturk771_reader, simverb3500dev_reader,\n", - " simverb3500test_reader, men_reader)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Dataset comparisons\n", - "\n", - "This section does some basic analysis of the datasets. The goal is to obtain a deeper understanding of what problem we're solving – what strengths and weaknesses the datasets have and how they relate to each other. For a full-fledged project, we would want to continue work like this and report on it in the paper, to provide context for the results." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_reader_name(reader):\n", - " \"\"\"\n", - " Return a cleaned-up name for the dataset iterator `reader`.\n", - " \"\"\"\n", - " return reader.__name__.replace(\"_reader\", \"\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Vocab overlap\n", - "\n", - "How many vocabulary items are shared across the datasets?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_reader_vocab(reader):\n", - " \"\"\"Return the set of words (str) in `reader`.\"\"\"\n", - " vocab = set()\n", - " for w1, w2, _ in reader():\n", - " vocab.add(w1)\n", - " vocab.add(w2)\n", - " return vocab" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_reader_vocab_overlap(readers=READERS):\n", - " \"\"\"\n", - " Get data on the vocab-level relationships between pairs of\n", - " readers. Returns a a pd.DataFrame containing this information.\n", - " \"\"\"\n", - " data = []\n", - " for r1, r2 in itertools.product(readers, repeat=2):\n", - " v1 = get_reader_vocab(r1)\n", - " v2 = get_reader_vocab(r2)\n", - " d = {\n", - " 'd1': get_reader_name(r1),\n", - " 'd2': get_reader_name(r2),\n", - " 'overlap': len(v1 & v2),\n", - " 'union': len(v1 | v2),\n", - " 'd1_size': len(v1),\n", - " 'd2_size': len(v2)}\n", - " data.append(d)\n", - " return pd.DataFrame(data)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "vocab_overlap = get_reader_vocab_overlap()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def vocab_overlap_crosstab(vocab_overlap):\n", - " \"\"\"\n", - " Return an intuitively formatted `pd.DataFrame` giving vocab-overlap\n", - " counts for all the datasets represented in `vocab_overlap`, the\n", - " output of `get_reader_vocab_overlap`.\n", - " \"\"\"\n", - " xtab = pd.crosstab(\n", - " vocab_overlap['d1'],\n", - " vocab_overlap['d2'],\n", - " values=vocab_overlap['overlap'],\n", - " aggfunc=np.mean)\n", - " # Blank out the upper right to reduce visual clutter:\n", - " for i in range(0, xtab.shape[0]):\n", - " for j in range(i+1, xtab.shape[1]):\n", - " xtab.iloc[i, j] = ''\n", - " return xtab" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "vocab_overlap_crosstab(vocab_overlap)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This looks reasonable. By design, the SimVerb dev and test sets have a lot of overlap. The other overlap numbers are pretty small, even adjusting for dataset size." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Pair overlap and score correlations\n", - "\n", - "How many word pairs are shared across datasets and, for shared pairs, what is the correlation between their scores? That is, do the datasets agree?" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_reader_pairs(reader):\n", - " \"\"\"\n", - " Return the set of alphabetically-sorted word (str) tuples\n", - " in `reader`\n", - " \"\"\"\n", - " return {tuple(sorted([w1, w2])): score for w1, w2, score in reader()}" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def get_reader_pair_overlap(readers=READERS):\n", - " \"\"\"Return a `pd.DataFrame` giving the number of overlapping\n", - " word-pairs in pairs of readers, along with the Spearman\n", - " correlations.\n", - " \"\"\"\n", - " data = []\n", - " for r1, r2 in itertools.product(READERS, repeat=2):\n", - " if r1.__name__ != r2.__name__:\n", - " d1 = get_reader_pairs(r1)\n", - " d2 = get_reader_pairs(r2)\n", - " overlap = []\n", - " for p, s in d1.items():\n", - " if p in d2:\n", - " overlap.append([s, d2[p]])\n", - " if overlap:\n", - " s1, s2 = zip(*overlap)\n", - " rho = spearmanr(s1, s2)[0]\n", - " else:\n", - " rho = None\n", - " # Canonical order for the pair:\n", - " n1, n2 = sorted([get_reader_name(r1), get_reader_name(r2)])\n", - " d = {\n", - " 'd1': n1,\n", - " 'd2': n2,\n", - " 'pair_overlap': len(overlap),\n", - " 'rho': rho}\n", - " data.append(d)\n", - " df = pd.DataFrame(data)\n", - " df = df.sort_values(['pair_overlap','d1','d2'], ascending=False)\n", - " # Return only every other row to avoid repeats:\n", - " return df[::2].reset_index(drop=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " display(get_reader_pair_overlap())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This looks reasonable: none of the datasets have a lot of overlapping pairs, so we don't have to worry too much about places where they give conflicting scores." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "## Evaluation\n", - "\n", - "This section builds up the evaluation code that you'll use for the homework and bake-off. For illustrations, I'll read in a VSM created from `data/vsmdata/giga_window5-scaled.csv.gz`:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "giga5 = pd.read_csv(\n", - " os.path.join(VSM_HOME, \"giga_window5-scaled.csv.gz\"), index_col=0)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dataset evaluation" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def word_similarity_evaluation(reader, df, distfunc=vsm.cosine):\n", - " \"\"\"\n", - " Word-similarity evalution framework.\n", - "\n", - " Parameters\n", - " ----------\n", - " reader : iterator\n", - " A reader for a word-similarity dataset. Just has to yield\n", - " tuples (word1, word2, score).\n", - "\n", - " df : pd.DataFrame\n", - " The VSM being evaluated.\n", - "\n", - " distfunc : function mapping vector pairs to floats.\n", - " The measure of distance between vectors. Can also be\n", - " `vsm.euclidean`, `vsm.matching`, `vsm.jaccard`, as well as\n", - " any other float-valued function on pairs of vectors.\n", - "\n", - " Raises\n", - " ------\n", - " ValueError\n", - " If `df.index` is not a subset of the words in `reader`.\n", - "\n", - " Returns\n", - " -------\n", - " float, data\n", - " `float` is the Spearman rank correlation coefficient between\n", - " the dataset scores and the similarity values obtained from\n", - " `df` using `distfunc`. This evaluation is sensitive only to\n", - " rankings, not to absolute values. `data` is a `pd.DataFrame`\n", - " with columns['word1', 'word2', 'score', 'distance'].\n", - "\n", - " \"\"\"\n", - " data = []\n", - " for w1, w2, score in reader():\n", - " d = {'word1': w1, 'word2': w2, 'score': score}\n", - " for w in [w1, w2]:\n", - " if w not in df.index:\n", - " raise ValueError(\n", - " \"Word '{}' is in the similarity dataset {} but not in the \"\n", - " \"DataFrame, making this evaluation ill-defined. Please \"\n", - " \"switch to a DataFrame with an appropriate vocabulary.\".\n", - " format(w, get_reader_name(reader)))\n", - " d['distance'] = distfunc(df.loc[w1], df.loc[w2])\n", - " data.append(d)\n", - " data = pd.DataFrame(data)\n", - " rho, pvalue = spearmanr(data['score'].values, data['distance'].values)\n", - " return rho, data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "rho, eval_df = word_similarity_evaluation(men_reader, giga5)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "rho" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "eval_df.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dataset error analysis\n", - "\n", - "For error analysis, we can look at the words with the largest delta between the gold score and the distance value in our VSM. We do these comparisons based on ranks, just as with our primary metric (Spearman $\\rho$), and we normalize both rankings so that they have a comparable number of levels." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def word_similarity_error_analysis(eval_df):\n", - " eval_df['distance_rank'] = _normalized_ranking(eval_df['distance'])\n", - " eval_df['score_rank'] = _normalized_ranking(eval_df['score'])\n", - " eval_df['error'] = abs(eval_df['distance_rank'] - eval_df['score_rank'])\n", - " return eval_df.sort_values('error')\n", - "\n", - "\n", - "def _normalized_ranking(series):\n", - " ranks = series.rank(method='dense')\n", - " return ranks / ranks.sum()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Best predictions:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "word_similarity_error_analysis(eval_df).head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Worst predictions:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "word_similarity_error_analysis(eval_df).tail()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Full evaluation" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "A full evaluation is just a loop over all the readers on which one want to evaluate, with a macro-average at the end:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def full_word_similarity_evaluation(df, readers=READERS, distfunc=vsm.cosine):\n", - " \"\"\"\n", - " Evaluate a VSM against all datasets in `readers`.\n", - "\n", - " Parameters\n", - " ----------\n", - " df : pd.DataFrame\n", - "\n", - " readers : tuple\n", - " The similarity dataset readers on which to evaluate.\n", - "\n", - " distfunc : function mapping vector pairs to floats.\n", - " The measure of distance between vectors. Can also be\n", - " `vsm.euclidean`, `vsm.matching`, `vsm.jaccard`, as well as\n", - " any other float-valued function on pairs of vectors.\n", - "\n", - " Returns\n", - " -------\n", - " pd.Series\n", - " Mapping dataset names to Spearman r values.\n", - "\n", - " \"\"\"\n", - " scores = {}\n", - " for reader in readers:\n", - " try:\n", - " score, _ = word_similarity_evaluation(reader, df, distfunc=distfunc)\n", - " scores[get_reader_name(reader)] = score\n", - " except Exception as e:\n", - " print(e)\n", - " scores[get_reader_name(reader)] = np.nan\n", - " series = pd.Series(scores, name='Spearman r')\n", - " series['Macro-average'] = series.mean()\n", - " return series" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " display(full_word_similarity_evaluation(giga5))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Homework questions\n", - "\n", - "Please embed your homework responses in this notebook, and do not delete any cells from the notebook. (You are free to add as many cells as you like as part of your responses.)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### PPMI as a baseline [0.5 points]\n", - "\n", - "The insight behind PPMI is a recurring theme in word representation learning, so it is a natural baseline for our task. For this question, write a function called `run_giga_ppmi_baseline` that does the following:\n", - "\n", - "1. Reads the Gigaword count matrix with a window of 20 and a flat scaling function into a `pd.DataFrame`s, as is done in the VSM notebooks. The file is `data/vsmdata/giga_window20-flat.csv.gz`, and the VSM notebooks provide examples of the needed code.\n", - "\n", - "1. Reweights this count matrix with PPMI.\n", - "\n", - "1. Evaluates this reweighted matrix using `full_word_similarity_evaluation`. The return value of `run_giga_ppmi_baseline` should be the return value of this call to `full_word_similarity_evaluation`.\n", - "\n", - "The goal of this question is to help you get more familiar with the code in `vsm` and the function `full_word_similarity_evaluation`.\n", - "\n", - "The function `test_run_giga_ppmi_baseline` can be used to test that you've implemented this specification correctly." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def run_giga_ppmi_baseline():\n", - " pass\n", - " ##### YOUR CODE HERE\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_run_giga_ppmi_baseline(func):\n", - " \"\"\"`func` should be `run_giga_ppmi_baseline\"\"\"\n", - " result = func()\n", - " ws_result = result.loc['wordsim353'].round(2)\n", - " ws_expected = 0.58\n", - " assert ws_result == ws_expected, \\\n", - " \"Expected wordsim353 value of {}; got {}\".format(\n", - " ws_expected, ws_result)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " test_run_giga_ppmi_baseline(run_giga_ppmi_baseline)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Gigaword with LSA at different dimensions [0.5 points]\n", - "\n", - "We might expect PPMI and LSA to form a solid pipeline that combines the strengths of PPMI with those of dimensionality reduction. However, LSA has a hyper-parameter $k$ – the dimensionality of the final representations – that will impact performance. For this problem, write a wrapper function `run_ppmi_lsa_pipeline` that does the following:\n", - "\n", - "1. Takes as input a count `pd.DataFrame` and an LSA parameter `k`.\n", - "1. Reweights the count matrix with PPMI.\n", - "1. Applies LSA with dimensionality `k`.\n", - "1. Evaluates this reweighted matrix using `full_word_similarity_evaluation`. The return value of `run_ppmi_lsa_pipeline` should be the return value of this call to `full_word_similarity_evaluation`.\n", - "\n", - "The goal of this question is to help you get a feel for how much LSA alone can contribute to this problem. \n", - "\n", - "The function `test_run_ppmi_lsa_pipeline` will test your function on the count matrix in `data/vsmdata/giga_window20-flat.csv.gz`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def run_ppmi_lsa_pipeline(count_df, k):\n", - " pass\n", - " ##### YOUR CODE HERE\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_run_ppmi_lsa_pipeline(func):\n", - " \"\"\"`func` should be `run_ppmi_lsa_pipeline`\"\"\"\n", - " giga20 = pd.read_csv(\n", - " os.path.join(VSM_HOME, \"giga_window20-flat.csv.gz\"), index_col=0)\n", - " results = func(giga20, k=10)\n", - " men_expected = 0.57\n", - " men_result = results.loc['men'].round(2)\n", - " assert men_result == men_expected,\\\n", - " \"Expected men value of {}; got {}\".format(men_expected, men_result)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " test_run_ppmi_lsa_pipeline(run_ppmi_lsa_pipeline)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Gigaword with GloVe [0.5 points]\n", - "\n", - "Can GloVe improve over the PPMI-based baselines we explored above? To begin to address this question, let's run GloVe and see how performance on our task changes throughout the optimization process.\n", - "\n", - "__Your task__: write a function `run_glove_wordsim_evals` that does the following:\n", - "\n", - "1. Has a parameter `n_runs` with default value `5`.\n", - "\n", - "1. Reads in `data/vsmdata/giga_window5-scaled.csv.gz`.\n", - "\n", - "1. Creates a `TorchGloVe` instance with `warm_start=True`, `max_iter=50`, and all other parameters set to their defaults.\n", - "\n", - "1. `n_runs` times, calls `fit` on your model and, after each, runs `full_word_similarity_evaluation` with default keyword parameters, extract the 'Macro-average' score, and add that score to a list.\n", - "\n", - "1. Returns the list of scores created.\n", - "\n", - "The trend should give you a sense for whether it is worth running GloVe for more iterations.\n", - "\n", - "Some implementation notes:\n", - "\n", - "* `TorchGloVe` will accept and return `pd.DataFrame` instances, so you shouldn't need to do any type conversions.\n", - "\n", - "* Performance will vary a lot for this function, so there is some uncertainty in the testing, but `run_glove_wordsim_evals` will at least check that you wrote a function with the right general logic." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def run_glove_wordsim_evals(n_runs=5):\n", - "\n", - " from torch_glove import TorchGloVe\n", - "\n", - " ##### YOUR CODE HERE\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_run_small_glove_evals(data):\n", - " \"\"\"`data` should be the return value of `run_glove_wordsim_evals`\"\"\"\n", - " assert isinstance(data, list), \\\n", - " \"`run_glove_wordsim_evals` should return a list\"\n", - " assert all(isinstance(x, float) for x in data), \\\n", - " (\"All the values in the list returned by `run_glove_wordsim_evals` \"\n", - " \"should be floats.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " glove_scores = run_glove_wordsim_evals()\n", - " print(glove_scores)\n", - " test_run_small_glove_evals(glove_scores)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Dice coefficient [0.5 points]\n", - "\n", - "Implement the Dice coefficient for real-valued vectors, as\n", - "\n", - "$$\n", - "\\textbf{dice}(u, v) = \n", - "1 - \\frac{\n", - " 2 \\sum_{i=1}^{n}\\min(u_{i}, v_{i})\n", - "}{\n", - " \\sum_{i=1}^{n} u_{i} + v_{i}\n", - "}$$\n", - " \n", - "You can use `test_dice_implementation` below to check that your implementation is correct." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def dice(u, v):\n", - " pass\n", - " ##### YOUR CODE HERE\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_dice_implementation(func):\n", - " \"\"\"`func` should be an implementation of `dice` as defined above.\"\"\"\n", - " X = np.array([\n", - " [ 4., 4., 2., 0.],\n", - " [ 4., 61., 8., 18.],\n", - " [ 2., 8., 10., 0.],\n", - " [ 0., 18., 0., 5.]])\n", - " assert func(X[0], X[1]).round(5) == 0.80198\n", - " assert func(X[1], X[2]).round(5) == 0.67568" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " test_dice_implementation(dice)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### t-test reweighting [2 points]\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The t-test statistic can be thought of as a reweighting scheme. For a count matrix $X$, row index $i$, and column index $j$:\n", - "\n", - "$$\\textbf{ttest}(X, i, j) = \n", - "\\frac{\n", - " P(X, i, j) - \\big(P(X, i, *)P(X, *, j)\\big)\n", - "}{\n", - "\\sqrt{(P(X, i, *)P(X, *, j))}\n", - "}$$\n", - "\n", - "where $P(X, i, j)$ is $X_{ij}$ divided by the total values in $X$, $P(X, i, *)$ is the sum of the values in row $i$ of $X$ divided by the total values in $X$, and $P(X, *, j)$ is the sum of the values in column $j$ of $X$ divided by the total values in $X$.\n", - "\n", - "For this problem, implement this reweighting scheme. You can use `test_ttest_implementation` below to check that your implementation is correct. You do not need to use this for any evaluations, though we hope you will be curious enough to do so!" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def ttest(df):\n", - " pass\n", - " ##### YOUR CODE HERE\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_ttest_implementation(func):\n", - " \"\"\"`func` should be `ttest`\"\"\"\n", - " X = pd.DataFrame(np.array([\n", - " [ 4., 4., 2., 0.],\n", - " [ 4., 61., 8., 18.],\n", - " [ 2., 8., 10., 0.],\n", - " [ 0., 18., 0., 5.]]))\n", - " actual = np.array([\n", - " [ 0.33056, -0.07689, 0.04321, -0.10532],\n", - " [-0.07689, 0.03839, -0.10874, 0.07574],\n", - " [ 0.04321, -0.10874, 0.36111, -0.14894],\n", - " [-0.10532, 0.07574, -0.14894, 0.05767]])\n", - " predicted = func(X)\n", - " assert np.array_equal(predicted.round(5), actual)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " test_ttest_implementation(ttest)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Enriching a VSM with subword information [2 points]\n", - "\n", - "It might be useful to combine character-level information with word-level information. To help you begin asssessing this idea, this question asks you to write a function that modifies an existing VSM so that the representation for each word $w$ is the element-wise sum of $w$'s original word-level representation with all the representations for the n-grams $w$ contains. \n", - "\n", - "The following starter code should help you structure this and clarify the requirements, and a simple test is included below as well.\n", - "\n", - "You don't need to write a lot of code; the motivation for this question is that the function you write could have practical value." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def subword_enrichment(df, n=4):\n", - " pass\n", - " # 1. Use `vsm.ngram_vsm` to create a character-level\n", - " # VSM from `df`, using the above parameter `n` to\n", - " # set the size of the ngrams.\n", - "\n", - " ##### YOUR CODE HERE\n", - "\n", - "\n", - " # 2. Use `vsm.character_level_rep` to get the representation\n", - " # for every word in `df` according to the character-level\n", - " # VSM you created above.\n", - "\n", - " ##### YOUR CODE HERE\n", - "\n", - "\n", - " # 3. For each representation created at step 2, add in its\n", - " # original representation from `df`. (This should use\n", - " # element-wise addition; the dimensionality of the vectors\n", - " # will be unchanged.)\n", - "\n", - " ##### YOUR CODE HERE\n", - "\n", - "\n", - " # 4. Return a `pd.DataFrame` with the same index and column\n", - " # values as `df`, but filled with the new representations\n", - " # created at step 3.\n", - "\n", - " ##### YOUR CODE HERE\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def test_subword_enrichment(func):\n", - " \"\"\"`func` should be an implementation of subword_enrichment as\n", - " defined above.\n", - " \"\"\"\n", - " vocab = [\"ABCD\", \"BCDA\", \"CDAB\", \"DABC\"]\n", - " df = pd.DataFrame([\n", - " [1, 1, 2, 1],\n", - " [3, 4, 2, 4],\n", - " [0, 0, 1, 0],\n", - " [1, 0, 0, 0]], index=vocab)\n", - " expected = pd.DataFrame([\n", - " [14, 14, 18, 14],\n", - " [22, 26, 18, 26],\n", - " [10, 10, 14, 10],\n", - " [14, 10, 10, 10]], index=vocab)\n", - " new_df = func(df, n=2)\n", - " assert np.array_equal(expected.columns, new_df.columns), \\\n", - " \"Columns are not the same\"\n", - " assert np.array_equal(expected.index, new_df.index), \\\n", - " \"Indices are not the same\"\n", - " assert np.array_equal(expected.values, new_df.values), \\\n", - " \"Co-occurrence values aren't the same\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " test_subword_enrichment(subword_enrichment)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Your original system [3 points]\n", - "\n", - "This question asks you to design your own model. You can of course include steps made above (ideally, the above questions informed your system design!), but your model should not be literally identical to any of the above models. Other ideas: retrofitting, autoencoders, GloVe, subword modeling, ... \n", - "\n", - "Requirements:\n", - "\n", - "1. Your code must operate on one or more of the count matrices in `data/vsmdata`. You can choose which subset of them; this is an important design feature of your system. __Other pretrained vectors cannot be introduced__.\n", - "\n", - "1. Retrofitting is permitted.\n", - "\n", - "1. Your code must be self-contained, so that we can work with your model directly in your homework submission notebook. If your model depends on external data or other resources, please submit a ZIP archive containing these resources along with your submission.\n", - "\n", - "In the cell below, please provide a brief technical description of your original system, so that the teaching team can gain an understanding of what it does. This will help us to understand your code and analyze all the submissions to identify patterns and strategies. We also ask that you report the best score your system got during development, just to help us understand how systems performed overall." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# PLEASE MAKE SURE TO INCLUDE THE FOLLOWING BETWEEN THE START AND STOP COMMENTS:\n", - "# 1) Textual description of your system.\n", - "# 2) The code for your original system.\n", - "# 3) The score achieved by your system in place of MY_NUMBER.\n", - "# With no other changes to that line.\n", - "# You should report your score as a decimal value <=1.0\n", - "# PLEASE MAKE SURE NOT TO DELETE OR EDIT THE START AND STOP COMMENTS\n", - "\n", - "# NOTE: MODULES, CODE AND DATASETS REQUIRED FOR YOUR ORIGINAL SYSTEM \n", - "# SHOULD BE ADDED BELOW THE 'IS_GRADESCOPE_ENV' CHECK CONDITION. DOING\n", - "# SO ABOVE THE CHECK MAY CAUSE THE AUTOGRADER TO FAIL.\n", - "\n", - "# START COMMENT: Enter your system description in this cell.\n", - "# My peak score was: MY_NUMBER\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - "\n", - "# STOP COMMENT: Please do not remove this comment." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Bake-off [1 point]\n", - "\n", - "For the bake-off, we will release two additional datasets. The announcement will go out on the discussion forum. We will also release reader code for these datasets that you can paste into this notebook. You will evaluate your custom model $M$ (from the previous question) on these new datasets using `full_word_similarity_evaluation`. Rules:\n", - "\n", - "1. Only one evaluation is permitted.\n", - "1. No additional system tuning is permitted once the bake-off has started.\n", - "\n", - "The cells below this one constitute your bake-off entry.\n", - "\n", - "People who enter will receive the additional homework point, and people whose systems achieve the top score will receive an additional 0.5 points. We will test the top-performing systems ourselves, and only systems for which we can reproduce the reported results will win the extra 0.5 points.\n", - "\n", - "Late entries will be accepted, but they cannot earn the extra 0.5 points. Similarly, you cannot win the bake-off unless your homework is submitted on time.\n", - "\n", - "The announcement will include the details on where to submit your entry." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Enter your bake-off assessment code into this cell.\n", - "# Please do not remove this comment.\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - " # Please enter your code in the scope of the above conditional.\n", - " ##### YOUR CODE HERE\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# On an otherwise blank line in this cell, please enter\n", - "# your \"Macro-average\" value as reported by the code above.\n", - "# Please enter only a number between 0 and 1 inclusive.\n", - "# Please do not remove this comment.\n", - "if 'IS_GRADESCOPE_ENV' not in os.environ:\n", - " pass\n", - " # Please enter your score in the scope of the above conditional.\n", - " ##### YOUR CODE HERE\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.7" - }, - "widgets": { - "state": {}, - "version": "1.1.2" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} \ No newline at end of file diff --git a/nli.py b/nli.py index 6fcd925..d2c9a78 100644 --- a/nli.py +++ b/nli.py @@ -10,7 +10,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" CONDITION_NAMES = [ diff --git a/nli_01_task_and_data.ipynb b/nli_01_task_and_data.ipynb index 3584c4c..9fe00bd 100644 --- a/nli_01_task_and_data.ipynb +++ b/nli_01_task_and_data.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -956,9 +956,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/nli_02_models.ipynb b/nli_02_models.ipynb index 27c7a96..1162a8c 100644 --- a/nli_02_models.ipynb +++ b/nli_02_models.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -833,9 +833,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stderr", @@ -1507,9 +1505,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/np_autoencoder.py b/np_autoencoder.py index f10335d..2f3e5bf 100644 --- a/np_autoencoder.py +++ b/np_autoencoder.py @@ -4,7 +4,7 @@ from sklearn.metrics import r2_score __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class Autoencoder(NNModelBase): diff --git a/np_glove.py b/np_glove.py index 933e041..654b0b0 100644 --- a/np_glove.py +++ b/np_glove.py @@ -6,7 +6,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class GloVe: diff --git a/np_model_base.py b/np_model_base.py index 398f173..42c3696 100644 --- a/np_model_base.py +++ b/np_model_base.py @@ -3,7 +3,7 @@ from utils import randvec, randmatrix, progress_bar, d_tanh __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class NNModelBase(object): diff --git a/np_rnn_classifier.py b/np_rnn_classifier.py index aacf7d5..7eb3dd6 100644 --- a/np_rnn_classifier.py +++ b/np_rnn_classifier.py @@ -4,7 +4,7 @@ from utils import softmax, safe_macro_f1 __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class RNNClassifier(NNModelBase): diff --git a/np_sgd_classifier.py b/np_sgd_classifier.py index ba54a21..8e4fde3 100644 --- a/np_sgd_classifier.py +++ b/np_sgd_classifier.py @@ -3,7 +3,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class BasicSGDClassifier(object): diff --git a/np_shallow_neural_classifier.py b/np_shallow_neural_classifier.py index 3d8a6f4..ca91beb 100644 --- a/np_shallow_neural_classifier.py +++ b/np_shallow_neural_classifier.py @@ -3,7 +3,7 @@ from utils import randvec, randmatrix, softmax, progress_bar, safe_macro_f1 __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class ShallowNeuralClassifier(NNModelBase): diff --git a/np_tree_nn.py b/np_tree_nn.py index 3f7a029..4527648 100644 --- a/np_tree_nn.py +++ b/np_tree_nn.py @@ -3,7 +3,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class TreeNN(NNModelBase): diff --git a/projects.md b/projects.md index 713b69f..11bb68f 100644 --- a/projects.md +++ b/projects.md @@ -1,7 +1,7 @@ # Final projects Christopher Potts
-CS224u, Stanford, Fall 2020 +CS224u, Stanford, Spring 2021 ## Contents @@ -26,7 +26,7 @@ CS224u, Stanford, Fall 2020 1. [Required authorship statement](#required-authorship-statement) 1. [Advice on scientific writing](#advice-on-scientific-writing) 1. [Some exceptionally well-written NLU papers](#some-exceptionally-well-written-nlu-papers) - 1. [Some CS224u papers that become publications](#some-cs224u-papers-that-become-publications) + 1. [Some CS224u papers that became publications](#some-cs224u-papers-that-became-publications) 1. [Beyond the final paper](#beyond-the-final-paper) 1. [Conference submissions](#conference-submissions) @@ -319,7 +319,7 @@ These papers are stand-outs for me not just because of the proposals they make, And check out this amazing contribution: [The Annotated Transformer](http://nlp.seas.harvard.edu/2018/04/03/attention.html) (Alexander Rush). -### Some CS224u papers that become publications +### Some CS224u papers that became publications Here is a selection of recent CS224u papers that evolved into published work: @@ -327,12 +327,16 @@ Here is a selection of recent CS224u papers that evolved into published work: * Benavidez, Susana and Andy Lapastora. 2019. Improving hate speech classification on Twitter. _Proceedings of LatinX in AI Research_. Vancouver. +* Chen, Xiaoyu and Rohan Badlani. 2020. [Relation extraction with contextualized relation embedding (CRE)](https://www.aclweb.org/anthology/2020.deelio-1.2). In _Proceedings of Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning Architectures_, 11–19. Association for Computational Linguistics. + * Kolchinski, Y. Alex and Christopher Potts. 2018. [Representing social media users for sarcasm detection](https://www.aclweb.org/anthology/D18-1140/). In _Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing_, 1115-1121. Brussels, Belgium: Association for Computational Linguistics. * Jiang, Hang; Yuxing Chen; Haoshen Hong; and Vivek Kulkarni. 2020. DialectGram: Automatic detection of dialectal variation at multiple geographic resolutions. In _Proceedings of the Society for Computation in Linguistics (SCiL) 2020_. New Orleans: Association for Computational Linguistics. * Li, Lucy and Julia Mendelsohn. 2019. [Using sentiment induction to understand variation in gendered online communities](https://www.aclweb.org/anthology/W19-0116/). In _Proceedings of the Society for Computation in Linguistics (SCiL) 2019_, 156–166. New York: Association for Computational Linguistics. +* Zhengxuan Wu, Desmond C. Ong. 2020. [Pragmatically informative color generation by grounding contextual modifiers](https://scholarworks.umass.edu/scil/vol4/iss1/54/). _Proceedings of the Society for Computation in Linguistics_, Vol. 4 , Article 54. + I'm being careful not to call these "published CS224u papers" because all of them went through substantial revisions before they were accepted. Some got shorter while retaining their original scope, whereas others grew in scope and got much longer. I should emphasize also that these papers all exceeded our expectations for course projects even when they were submitted, and they matured afterwords, so the above are not examples of what we're expecting by the end of the course itself. These are more like things to aspire to longer term. diff --git a/rel_ext.py b/rel_ext.py index 2b3b67c..b101278 100644 --- a/rel_ext.py +++ b/rel_ext.py @@ -9,7 +9,7 @@ from sklearn.model_selection import train_test_split __author__ = "Bill MacCartney and Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" Example = namedtuple('Example', diff --git a/rel_ext_01_task.ipynb b/rel_ext_01_task.ipynb index da08d6b..aafbda2 100644 --- a/rel_ext_01_task.ipynb +++ b/rel_ext_01_task.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Bill MacCartney and Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -1450,7 +1450,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -1458,5 +1458,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/rel_ext_02_experiments.ipynb b/rel_ext_02_experiments.ipynb index 947555b..4d7d14e 100644 --- a/rel_ext_02_experiments.ipynb +++ b/rel_ext_02_experiments.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Bill MacCartney and Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -808,13 +808,7 @@ " 1.000 KBTriple(rel='nationality', sbj='Ramanathapuram_district', obj='Tamil_Nadu')\n", "\n", "Highest probability examples for relation parents:\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "\n", " 1.000 KBTriple(rel='parents', sbj='Philip_II_of_Macedon', obj='Alexander_the_Great')\n", " 1.000 KBTriple(rel='parents', sbj='Lincoln_Borglum', obj='Gutzon_Borglum')\n", " 1.000 KBTriple(rel='parents', sbj='Gutzon_Borglum', obj='Lincoln_Borglum')\n", @@ -915,7 +909,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -923,5 +917,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/requirements.txt b/requirements.txt index 2c04d0b..1a69058 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,23 +3,28 @@ # Only people working in their own virtual environments should install # them via this script. # -# numpy>=1.15.0 -# scipy>=1.1.0 -# matplotlib>=3.0.0 -# scikit-learn>=0.20.0 -# nltk>=3.4.0 +# numpy>=1.19.0 +# scipy>=1.5.0 +# matplotlib>=3.3.0 +# scikit-learn>=0.23.0 +# nltk>=3.5.0 # pytest>=4.0.0 # jupyter>=1.0.0 -# pandas>=0.25.0 +# pandas>=1.1.2 -###################################################################### -# For NLTK, the data distibution needs to be downloaded separately: -# -# https://www.nltk.org/data.html ###################################################################### # PyTorch is required. For installation instructions, see # -# If you're using Anaconda, we suggest +# https://pytorch.org/get-started/locally/ +# +# For local usage, the followng should suffice # # conda install pytorch torchvision -c pytorch + +###################################################################### +# transformers +# +# The Hugging Face transformers library is required: +# +# transformers==4.3.3 diff --git a/retrofitting.py b/retrofitting.py index 2a7b99b..c1784c6 100644 --- a/retrofitting.py +++ b/retrofitting.py @@ -5,7 +5,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class Retrofitter(object): diff --git a/setup.ipynb b/setup.ipynb index 92e0314..d3eae6b 100644 --- a/setup.ipynb +++ b/setup.ipynb @@ -9,12 +9,12 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -36,7 +36,7 @@ "1. [Additional installations](#Additional-installations)\n", " 1. [Installing the package requirements](#Installing-the-package-requirements)\n", " 1. [PyTorch](#PyTorch)\n", - " 1. [NLTK data](#NLTK-data)\n", + " 1. [Hugging Face transformers](#Hugging-Face-transformers)\n", "1. [Jupyter notebooks](#Jupyter-notebooks)" ] }, @@ -46,13 +46,13 @@ "source": [ "## Anaconda\n", "\n", - "We recommend installing [the free Anaconda Python distribution](https://www.anaconda.com/distribution/), which includes IPython, Numpy, Scipy, matplotlib, scikit-learn, NLTK, and many other useful packages. This is not required, but it's an easy way to get all these packages installed. Unless you're very comfortable with Python package management and like installing things, this is the option for you!\n", + "We recommend installing [the free Anaconda Python distribution](https://www.anaconda.com/products/individual), which includes IPython, Numpy, Scipy, matplotlib, scikit-learn, NLTK, and many other useful packages. This is not required, but it's an easy way to get all these packages installed. Unless you're very comfortable with Python package management and like installing things, this is the option for you!\n", "\n", - "Please be sure that you download the __Python 3__ version, which currently installs Python 3.7. __The codebase is not compatible with Python 2__.\n", + "Please be sure that you download the __Python 3__ version, which currently installs Python 3.8. __Our codebase is not compatible with Python 2__.\n", "\n", - "One you have Anaconda installed, it makes sense to create a virtual environment for the course. In a terminal, run\n", + "One you have Anaconda installed, create a virtual environment for the course. In a terminal, run\n", "\n", - "```conda create -n nlu python=3.7 anaconda```\n", + "```conda create -n nlu python=3.8 anaconda```\n", "\n", "to create an environment called `nlu`.\n", "\n", @@ -107,7 +107,11 @@ "source": [ "## Additional installations\n", "\n", - "Be sure to do these additional installations from __inside your virtual environment__ for the course!" + "Be sure to do these additional installations from [inside your virtual environment](#Anaconda) for the course! Before you proceed from here, perhaps run\n", + "\n", + "```conda activate nlu```\n", + "\n", + "to make sure you are in that environment." ] }, { @@ -116,7 +120,7 @@ "source": [ "### Installing the package requirements\n", "\n", - "If you are running Anaconda, then all of the requirements are already met, except for PyTorch and NLTK data, discussed below. \n", + "If you are running Anaconda, then most of the requirements are already met – you'll just need to add PyTorch and the Hugging Face `transformers` library, both discussed below. \n", "\n", "People who aren't using Anaconda should edit `requirements.txt` so that it installs all the prerequisites that come with Anaconda and then run\n", "\n", @@ -139,21 +143,21 @@ "\n", "https://pytorch.org/get-started/locally/\n", "\n", - "For this course, you should be running at least version `1.4.0`:" + "For this course, you should be running at least version `1.7.0` and preferably `1.8.0`:" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'1.4.0'" + "'1.8.0'" ] }, - "execution_count": 1, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -168,9 +172,59 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### NLTK data\n", + "If you decide to use a different version of PyTorch, you might encounter problems. The library is progressing fast and we cannot guarantee backward compatibility for versions before `1.7.0`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Hugging Face transformers" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will be making extensive use of the [Hugging Face](https://huggingface.co/) `transformers` library. To install it, run the following from inside your virtual environment:\n", "\n", - "Anaconda comes with NLTK but not with its data distribution. To install that, open a Python interpreter and run `import nltk; nltk.download()`. If you decide to download the data to a different directory than the default, then you'll have to set `NLTK_DATA` in your shell profile. (If that doesn't make sense to you, then we recommend choosing the default download directory!)" + "```pip install transformers==4.3.3```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And then verify that you are running the correct version here:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'4.3.3'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import transformers\n", + "\n", + "transformers.__version__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This library is changing even faster that PyTorch, so it is crucial that you run this version for our coursework." ] }, { @@ -195,7 +249,9 @@ "\n", "(If you named your environment something other than `nlu`, then change the `--name` and `--display-name` values.) \n", "\n", - "[Additional discussion of Jupyter and kernels.](https://stackoverflow.com/questions/39604271/conda-environments-not-showing-up-in-jupyter-notebook)" + "[Additional discussion of Jupyter and kernels.](https://stackoverflow.com/questions/39604271/conda-environments-not-showing-up-in-jupyter-notebook)\n", + "\n", + "For some tips on getting started with notebooks, see [our Jupyter tutorial](tutorial_jupyter_notebooks.ipynb)." ] } ], @@ -215,9 +271,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 1 + "nbformat_minor": 4 } diff --git a/sst.py b/sst.py index 3ac7559..91caef7 100644 --- a/sst.py +++ b/sst.py @@ -1,9 +1,6 @@ -from collections import Counter, namedtuple -from nltk.tree import Tree import numpy as np import os import pandas as pd -import random from sklearn.model_selection import train_test_split from sklearn.feature_extraction import DictVectorizer from sklearn.linear_model import LogisticRegression @@ -12,140 +9,111 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" -def sentiment_treebank_reader(src_filename, class_func=None): +def sentiment_reader(src_filename, include_subtrees=True, dedup=False): """ - Iterator for the Penn-style distribution of the Stanford - Sentiment Treebank. The iterator yields (tree, label) pairs. - - The labels are strings. They do not make sense as a linear order - because negative ('0', '1'), neutral ('2'), and positive ('3','4') - do not form a linear order conceptually, and because '0' is - stronger than '1' but '4' is stronger than '3'. + Iterator for our distribution of the SST-3 and other files in + that format. Parameters ---------- src_filename : str Full path to the file to be read. - class_func : None, or function mapping labels to labels or None - If this is None, then the original 5-way labels are returned. - Other options: `binary_class_func` and `ternary_class_func` - (or you could write your own). + include_subtrees : bool + If True, then the subtrees are returned as separate examples. + This affects only the train split. For dev and test, only + the full examples are included. + + dedup : bool + If True, only one copy of each (example, label) pair is included. + This mainly affects the train set, though there is one repeated + example in the dev set. Yields ------ - (tree, label) - nltk.Tree, str in {'0','1','2','3','4'} + pd.DataFrame with columns ['example_id', 'sentence', 'label'] """ - if class_func is None: - class_func = lambda x: x - with open(src_filename, encoding='utf8') as f: - for line in f: - tree = Tree.fromstring(line) - label = class_func(tree.label()) - # As in the paper, if the root node doesn't fall into any - # of the classes for this version of the problem, then - # we drop the example: - if label: - for subtree in tree.subtrees(): - subtree.set_label(class_func(subtree.label())) - yield (tree, label) - - -def binary_class_func(y): - """ - Define a binary SST task. + df = pd.read_csv(src_filename) + if not include_subtrees: + df = df[df.is_subtree == 0] + if dedup: + df = df.groupby(['sentence', 'label']).apply(lambda x: x.iloc[0]) + df = df.reset_index(drop=True) + return df - Parameters - ---------- - y : str - Assumed to be one of the SST labels. - Returns - ------- - str or None - None values are ignored by `build_dataset` and thus left out of - the experiments. +def train_reader(sst_home, include_subtrees=False, dedup=False): + """ + Convenience function for reading the SST-3 train file. """ - if y in ("0", "1"): - return "negative" - elif y in ("3", "4"): - return "positive" - else: - return None + src = os.path.join(sst_home, 'sst3-train.csv') + return sentiment_reader( + src, include_subtrees=include_subtrees, dedup=dedup) -def ternary_class_func(y): +def dev_reader(sst_home, include_subtrees=False, dedup=False): """ - Define a binary SST task. Just like `binary_class_func` except - input '2' returns 'neutral'. + Convenience function for reading the SST-3 dev file. """ - if y in ("0", "1"): - return "negative" - elif y in ("3", "4"): - return "positive" - else: - return "neutral" + src = os.path.join(sst_home, 'sst3-dev.csv') + return sentiment_reader( + src, include_subtrees=include_subtrees, dedup=dedup) -def train_reader(sst_home, **kwargs): +def test_reader(sst_home, include_subtrees=False, dedup=False): """ - Convenience function for reading the train file, full-trees only. + Convenience function for reading the SST-3 test file, unlabeled. + This function should be used only for the final stages of a + project, to obtain a submission to be evaluated. If you need + to do an evaluation yourself with the labeled dataset, use + `sentiment_reader` pointing to the labeled version of this + dataset. """ - src = os.path.join(sst_home, 'train.txt') - return sentiment_treebank_reader(src, **kwargs) + src = os.path.join(sst_home, 'sst3-test-unlabeled.csv') + return sentiment_reader( + src, include_subtrees=include_subtrees, dedup=dedup) -def dev_reader(sst_home, **kwargs): +def bakeoff_dev_reader(sst_home, include_subtrees=False, dedup=False): """ - Convenience function for reading the dev file, full-trees only. + Convenience function for reading the bakeoff dev file. """ - src = os.path.join(sst_home, 'dev.txt') - return sentiment_treebank_reader(src, **kwargs) + src = os.path.join(sst_home, 'cs224u-sentiment-dev.csv') + return sentiment_reader( + src, include_subtrees=include_subtrees, dedup=dedup) -def test_reader(sst_home, **kwargs): +def bakeoff_test_reader(sst_home, include_subtrees=False, dedup=False): """ - Convenience function for reading the test file, full-trees only. - This function should be used only for the final stages of a project, - to obtain final results. + Convenience function for reading the bakeoff test file, unlabeled. """ - src = os.path.join(sst_home, 'test.txt') - return sentiment_treebank_reader(src, **kwargs) + src = os.path.join(sst_home, 'cs224u-sentiment-test-unlabeled.csv') + return sentiment_reader( + src, include_subtrees=include_subtrees, dedup=dedup) -def build_dataset(sst_home, reader, phi, class_func, vectorizer=None, vectorize=True): +def build_dataset(dataframes, phi, vectorizer=None, vectorize=True): """ Core general function for building experimental datasets. Parameters ---------- - sst_home : str - Full path to the 'trees' directory for SST. - - reader : iterator or iterable of iterators - Should be `train_reader`, `dev_reader`, or another function - defined in those terms, or a list/tuple of such functions. - This is the dataset we'll be featurizing. + dataframes : pd.DataFrame or list of pd.DataFrame + The dataset or datasets to process, as read in by + `sentiment_reader`. phi : feature function - Any function that takes an `nltk.Tree` instance as input - and returns a bool/int/float-valued dict as output. - - class_func : function on the SST labels - Any function like `binary_class_func` or `ternary_class_func`. - This modifies the SST labels based on the experimental - design. If `class_func` returns None for a label, then that - item is ignored. + Any function that takes a string as input and returns a + bool/int/float-valued dict as output. vectorizer : sklearn.feature_extraction.DictVectorizer If this is None, then a new `DictVectorizer` is created and @@ -168,24 +136,24 @@ def build_dataset(sst_home, reader, phi, class_func, vectorizer=None, vectorize= 'raw_examples' (the `nltk.Tree` objects, for error analysis). """ - labels = [] - feat_dicts = [] - raw_examples = [] + if isinstance(dataframes, (list, tuple)): + df = pd.concat(dataframes) + else: + df = dataframes + + raw_examples = list(df.sentence.values) - if isinstance(reader, (list, tuple)): - readers = reader + feat_dicts = list(df.sentence.apply(phi).values) + + if 'label' in df.columns: + labels = list(df.label.values) else: - readers = [reader] + labels = None - for reader in readers: - for tree, label in reader(sst_home, class_func=class_func): - labels.append(label) - feat_dicts.append(phi(tree)) - raw_examples.append(tree) feat_matrix = None if vectorize: # In training, we want a new vectorizer: - if vectorizer == None: + if vectorizer is None: vectorizer = DictVectorizer(sparse=False) feat_matrix = vectorizer.fit_transform(feat_dicts) # In assessment, we featurize using the existing vectorizer: @@ -193,6 +161,7 @@ def build_dataset(sst_home, reader, phi, class_func, vectorizer=None, vectorize= feat_matrix = vectorizer.transform(feat_dicts) else: feat_matrix = feat_dicts + return {'X': feat_matrix, 'y': labels, 'vectorizer': vectorizer, @@ -200,26 +169,25 @@ def build_dataset(sst_home, reader, phi, class_func, vectorizer=None, vectorize= def experiment( - sst_home, + train_dataframes, phi, train_func, - train_reader=train_reader, - assess_reader=None, + assess_dataframes=None, train_size=0.7, - class_func=binary_class_func, score_func=utils.safe_macro_f1, vectorize=True, verbose=True, random_state=None): """ - Generic experimental framework for SST. Either assesses with a - random train/test split of `train_reader` or with `assess_reader` if + Generic experimental framework. Either assesses with a random + train/test split of `train_reader` or with `assess_reader` if it is given. Parameters ---------- - sst_home : str - Full path to the 'trees' directory for SST. + train_dataframes : pd.DataFrame or list of pd.DataFrame + The dataset or datasets to process, as read in by + `sentiment_reader`. phi : feature function Any function that takes an `nltk.Tree` instance as input @@ -230,45 +198,37 @@ def experiment( as its values and returns a fitted model with a `predict` function that operates on feature matrices. - train_reader : SST iterator (default: `train_reader`) - Iterator for training data. - - assess_reader : iterator or None (default: None) - If None, then the data from `train_reader` are split into + assess_dataframes : pd.DataFrame, list of pd.DataFrame or None + If None, then the df from `train_dataframes` is split into a random train/test split, with the the train percentage determined by `train_size`. If not None, then this should - be an iterator for assessment data (e.g., `dev_reader`). + be a dataset or datasets to process, as read in by + `sentiment_reader`. Each such dataset will be read and + used in a separate evaluation. train_size : float (default: 0.7) If `assess_reader` is None, then this is the percentage of `train_reader` devoted to training. If `assess_reader` is not None, then this value is ignored. - class_func : function on the SST labels - Any function like `binary_class_func` or `ternary_class_func`. - This modifies the SST labels based on the experimental - design. If `class_func` returns None for a label, then that - item is ignored. - score_metric : function name (default: `utils.safe_macro_f1`) This should be an `sklearn.metrics` scoring function. The default is weighted average F1 (macro-averaged F1). For comparison with the SST literature, `accuracy_score` might - be used instead. For micro-averaged F1, use - (lambda y, y_pred : f1_score(y, y_pred, average='micro', pos_label=None)) - For other metrics that can be used here, see + be used instead. For other metrics that can be used here, see http://scikit-learn.org/stable/modules/classes.html#module-sklearn.metrics vectorize : bool - Whether to use a DictVectorizer. Set this to False for - deep learning models that process their own input. + Whether to use a DictVectorizer. Set this to False for + deep learning models that process their own input. verbose : bool (default: True) Whether to print out the model assessment to standard output. Set to False for statistical testing via repeated runs. random_state : int or None - Optionally set the random seed for consistent sampling. + Optionally set the random seed for consistent sampling + where random train/test splits are being created. Prints ------- @@ -284,63 +244,84 @@ def experiment( 'model': trained model 'phi': the function used for featurization 'train_dataset': a dataset as returned by `build_dataset` - 'assess_dataset': a dataset as returned by `build_dataset` - 'predictions': predictions on the assessment data + 'assess_datasets': list of datasets as returned by `build_dataset` + 'predictions': list of lists of predictions on the assessment datasets 'metric': `score_func.__name__` - 'score': the `score_func` score on the assessment data + 'score': the `score_func` score on each of the assessment datasets """ # Train dataset: train = build_dataset( - sst_home, - train_reader, + train_dataframes, phi, - class_func, vectorizer=None, vectorize=vectorize) + # Manage the assessment set-up: X_train = train['X'] y_train = train['y'] raw_train = train['raw_examples'] - if assess_reader == None: + assess_datasets = [] + if assess_dataframes is None: X_train, X_assess, y_train, y_assess, raw_train, raw_assess = train_test_split( X_train, y_train, raw_train, - train_size=train_size, test_size=None, random_state=random_state) - assess = { + train_size=train_size, + test_size=None, + random_state=random_state) + assess_datasets.append({ 'X': X_assess, 'y': y_assess, 'vectorizer': train['vectorizer'], - 'raw_examples': raw_assess} + 'raw_examples': raw_assess}) else: - # Assessment dataset using the training vectorizer: - assess = build_dataset( - sst_home, - assess_reader, - phi, - class_func, - vectorizer=train['vectorizer'], - vectorize=vectorize) - X_assess, y_assess = assess['X'], assess['y'] + if not isinstance(assess_dataframes, (tuple, list)): + assess_dataframes = [assess_dataframes] + for assess_df in assess_dataframes: + # Assessment dataset using the training vectorizer: + assess = build_dataset( + assess_df, + phi, + vectorizer=train['vectorizer'], + vectorize=vectorize) + assess_datasets.append(assess) + # Train: mod = train_func(X_train, y_train) - # Predictions: - predictions = mod.predict(X_assess) - # Report: - if verbose: - print(classification_report(y_assess, predictions, digits=3)) - # Return the overall score and experimental info: + + # Predictions if we have labels: + predictions = [] + scores = [] + for dataset_num, assess in enumerate(assess_datasets, start=1): + preds = mod.predict(assess['X']) + if assess['y'] is None: + predictions.append(None) + scores.append(None) + else: + if verbose: + if len(assess_datasets) > 1: + print("Assessment dataset {}".format(dataset_num)) + print(classification_report(assess['y'], preds, digits=3)) + predictions.append(preds) + scores.append(score_func(assess['y'], preds)) + true_scores = [s for s in scores if s is not None] + if len(true_scores) > 1 and verbose: + mean_score = np.mean(true_scores) + print("Mean of macro-F1 scores: {0:.03f}".format(mean_score)) + + + # Return the overall scores and other experimental info: return { 'model': mod, 'phi': phi, 'train_dataset': train, - 'assess_dataset': assess, + 'assess_datasets': assess_datasets, 'predictions': predictions, 'metric': score_func.__name__, - 'score': score_func(y_assess, predictions)} + 'scores': scores} def compare_models( - sst_home, + dataframes, phi1, train_func1, phi2=None, @@ -349,9 +330,7 @@ def compare_models( vectorize2=True, stats_test=scipy.stats.wilcoxon, trials=10, - reader=train_reader, train_size=0.7, - class_func=binary_class_func, score_func=utils.safe_macro_f1): """ Wrapper for comparing models. The parameters are like those of @@ -359,8 +338,9 @@ def compare_models( Parameters ---------- - sst_home : str - Full path to the 'trees' directory for SST. + dataframes : pd.DataFrame or list of pd.DataFrame + The dataset or datasets to process, as read in by + `sentiment_reader`. phi1, phi2 Just like `phi` for `experiment`. `phi1` defaults to @@ -384,13 +364,7 @@ def compare_models( with `train_size` controlling the amount of training data. train_size : float - Percentage of data o use for training. - - class_func : function on the SST labels - Any function like `binary_class_func` or `ternary_class_func`. - This modifies the SST labels based on the experimental - design. If `class_func` returns None for a label, then that - item is ignored. + Percentage of data to use for training. Prints ------ @@ -401,94 +375,60 @@ def compare_models( ------- (np.array, np.array, float) The first two are the scores from each model (length `trials`), - and the third is the p-value returned by stats_test. + and the third is the p-value returned by `stats_test`. """ if phi2 == None: phi2 = phi1 if train_func2 == None: train_func2 = train_func1 - experiments1 = [experiment(sst_home, - train_reader=reader, + experiments1 = [experiment(dataframes, phi=phi1, train_func=train_func1, - class_func=class_func, score_func=score_func, vectorize=vectorize1, verbose=False) for _ in range(trials)] - experiments2 = [experiment(sst_home, - train_reader=reader, + experiments2 = [experiment(dataframes, phi=phi2, train_func=train_func2, - class_func=class_func, score_func=score_func, vectorize=vectorize2, verbose=False) for _ in range(trials)] - scores1 = np.array([d['score'] for d in experiments1]) - scores2 = np.array([d['score'] for d in experiments2]) + scores1 = np.array([d['scores'][0] for d in experiments1]) + scores2 = np.array([d['scores'][0] for d in experiments2]) # stats_test returns (test_statistic, p-value). We keep just the p-value: pval = stats_test(scores1, scores2)[1] # Report: - print('Model 1 mean: %0.03f' % scores1.mean()) - print('Model 2 mean: %0.03f' % scores2.mean()) - print('p = %0.03f' % pval if pval >= 0.001 else 'p < 0.001') + print('Model 1 mean: {0:.03f}'.format(scores1.mean())) + print('Model 2 mean: {0:.03f}'.format(scores2.mean())) + print('p = {0:.03f}'.format(pval if pval >= 0.001 else 'p < 0.001')) # Return the scores for later analysis, and the p value: - return (scores1, scores2, pval) + return scores1, scores2, pval -def build_rnn_dataset(sst_home, reader, class_func=binary_class_func): +def build_rnn_dataset(dataframes, tokenizer=lambda s: s.split()): """ - Given an SST reader, return the `class_func` version of the - dataset as (X, y) training pair. + Given an SST reader, return the dataset as (X, y) training pairs. Parameters ---------- - sst_home : str - Full path to the 'trees' directory for SST. - - reader : train_reader or dev_reader + dataframes : pd.DataFrame or list of pd.DataFrame + The dataset or datasets to process, as read in by + `sentiment_reader`. - class_func : function on the SST labels + tokenizer : function from str to list of str + Defaults to a whitespace tokenizer. Returns ------- X, y - Where X is a list of list of str, and y is the output label list. + Where X is a list of list of str, and y is the output label list. """ - r = reader(sst_home, class_func=class_func) - data = [(tree.leaves(), label) for tree, label in r] - X, y = zip(*data) - return list(X), list(y) - - -def build_tree_dataset(sst_home, reader, class_func=binary_class_func): - """ - Given an SST reader, return the `class_func` version of the - dataset. The root node of each tree (`tree.label()`) is set to - the class for that tree. We also return the label vector for - assessment. - - Parameters - ---------- - sst_home : str - Full path to the 'trees' directory for SST. - - reader : train_reader or dev_reader - - class_func : function on the SST labels - - Returns - ------- - X, y - Where X is a list of `nltk.tree.Tree`, and y is the output - label list. - - """ - data = [] - labels = [] - for (tree, label) in reader(sst_home, class_func=class_func): - tree.set_label(label) - data.append(tree) - labels.append(label) - return data, labels + if isinstance(dataframes, (list, tuple)): + df = pd.concat(dataframes) + else: + df = dataframes + X = list(df.sentence.apply(tokenizer)) + y = list(df.label.values) + return X, y diff --git a/sst_01_overview.ipynb b/sst_01_overview.ipynb index bc249f0..3d84ef4 100644 --- a/sst_01_overview.ipynb +++ b/sst_01_overview.ipynb @@ -18,7 +18,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -32,16 +32,13 @@ "## Contents\n", "\n", "1. [Overview of this unit](#Overview-of-this-unit)\n", - "1. [Paths through the material](#Paths-through-the-material)\n", - "1. [Overview of this notebook](#Overview-of-this-notebook)\n", - "1. [The complexity of sentiment analysis](#The-complexity-of-sentiment-analysis)\n", "1. [Set-up](#Set-up)\n", "1. [Data readers](#Data-readers)\n", - " 1. [Main readers](#Main-readers)\n", - " 1. [Methodological notes](#Methodological-notes)\n", - "1. [Modeling the SST labels](#Modeling-the-SST-labels)\n", - " 1. [Train label distributions](#Train-label-distributions)\n", - " 1. [Dev label distributions](#Dev-label-distributions)" + " 1. [Train split](#Train-split)\n", + " 1. [Root-only formulation](#Root-only-formulation)\n", + " 1. [Including subtrees](#Including-subtrees)\n", + " 1. [Dev and test splits](#Dev-and-test-splits)\n", + "1. [Tokenization](#Tokenization)" ] }, { @@ -62,7 +59,6 @@ " * Hand-built feature functions with (mostly linear) classifiers\n", " * Dense feature representations derived from VSMs as we built them in the previous unit\n", " * Recurrent neural networks (RNNs)\n", - " * Tree-structured neural networks\n", " \n", "* Begin discussing and implementing responsible methods for __hyperparameter optimization__ and __classifier assessment and comparison__.\n", "\n", @@ -77,51 +73,34 @@ } }, "source": [ - "## Paths through the material\n", - "\n", - "* If you're relatively new to supervised learning, we suggest studying the details of this notebook closely and following the links to [additional resources](#Additional-sentiment-resources). \n", + "## Set-up\n", "\n", - "* If you're familiar with supervised learning, then you can focus right away on innovative feature representations and modeling. \n", + "* Make sure your environment includes all the requirements for [the cs224u repository](https://github.com/cgpotts/cs224u).\n", "\n", - "* As of this writing, the state-of-the-art for the SST seems to be around 88% accuracy for the binary problem and 48% accuracy for the five-class problem. Perhaps you can best these numbers!" + "* If you haven't already, download [the course data](http://web.stanford.edu/class/cs224u/data/data.tgz), unpack it, and place it in the directory containing the course repository – the same directory as this notebook. (If you want to put it somewhere else, change `SST_HOME` below.)" ] }, { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], "source": [ - "## Overview of this notebook\n", - "\n", - "This is the first notebook in this unit. It does two things:\n", + "from nltk.tokenize.treebank import TreebankWordDetokenizer\n", + "from nltk.tokenize.treebank import TreebankWordTokenizer\n", + "import os\n", + "import pandas as pd\n", "\n", - "* Introduces sentiment analysis as a task.\n", - "* Introduces the SST and our tools for reading that corpus. " + "import sst" ] }, { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], "source": [ - "## The complexity of sentiment analysis\n", - "\n", - "Sentiment analysis seems simple at first but turns out to exhibit all of the complexity of full natural language understanding. To see this, consider how your intuitions about the sentiment of the following sentences can change depending on perspective, social relationships, tone of voice, and other aspects of the context of utterance:\n", - "\n", - "1. There was an earthquake in LA.\n", - "1. The team failed the physical challenge. (We win/lose!)\n", - "1. They said it would be great. They were right/wrong.\n", - "1. Many consider the masterpiece bewildering, boring, slow-moving or annoying.\n", - "1. The party fat-cats are sipping their expensive, imported wines.\n", - "1. Oh, you're terrible!\n", - "\n", - "SST mostly steers around these challenges by including only focused, evaluative texts (sentences from movie reviews), but you should have them in mind if you consider new domains and applications for the ideas." + "SST_HOME = os.path.join('data', 'sentiment')" ] }, { @@ -132,531 +111,792 @@ } }, "source": [ - "## Set-up\n", + "## Data readers\n", "\n", - "* Make sure your environment includes all the requirements for [the cs224u repository](https://github.com/cgpotts/cs224u).\n", + "Our SST distribution is the ternary version of the problem (SST-3). It consists of train/dev/test files with the following columns:\n", "\n", - "* If you haven't already, download [the course data](http://web.stanford.edu/class/cs224u/data/data.tgz), unpack it, and place it in the directory containing the course repository – the same directory as this notebook. (If you want to put it somewhere else, change `SST_HOME` below.)" + "1. `example_id`: a string with the format 'N-S' where N is the example number and S is the index for the subtree in example N. Both N and S are five-digit numbers with 0-padding.\n", + "2. `sentence`: a string giving the example sentence.\n", + "3. `label`: a string giving the label: `'positive'`, `'negative'`, or `'neutral'`. This value is derived from the original SST by mapping labels 0 and 1 to `'negative'`, label 2 to `'neutral'`, and labels 3 and 4 to `'positive'`.\n", + "4. `is_subtree`: the integer `1` if the example is a (proper) subtree, else `0`. This affects only the train file. Our dev and test splits contain no subtrees – full examples only – and hence `is_subtree` is always `0` for them." ] }, { - "cell_type": "code", - "execution_count": 2, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "from nltk.tree import Tree\n", - "import os\n", - "import pandas as pd\n", - "import sst" + "### Train split" ] }, { - "cell_type": "code", - "execution_count": 3, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "SST_HOME = os.path.join('data', 'trees')" + "When reading in the train split, you have a few options. " ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ - "## Data readers\n", - "\n", - "* The train/dev/test SST distribution contains files that are lists of trees where the part-of-speech tags have been replaced with sentiment scores `0...4`:\n", - " * `0` and `1` are negative labels.\n", - " * `2` is a neutral label.\n", - " * `3` and `4` are positive labels. \n", - "\n", - "* Our readers are iterators that yield `(tree, score)` pairs, where `tree` is an [NLTK Tree](http://www.nltk.org/_modules/nltk/tree.html) instance and `score` is a string." + "#### Root-only formulation" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ - "### Main readers\n", - "\n", - "We'll mainly work with `sst.train_reader` and `sst.dev_reader`." + "The default will include only full examples and retain duplicate examples:" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ - "tree, score = next(sst.train_reader(SST_HOME))" + "train_df = sst.train_reader(SST_HOME)" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 6, "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'example_id': '04162-00001',\n", + " 'sentence': \"One can only assume that the jury who bestowed star Hoffman 's brother Gordy with the Waldo Salt Screenwriting award at 2002 's Sundance Festival were honoring an attempt to do something different over actually pulling it off\",\n", + " 'label': 'negative',\n", + " 'is_subtree': 0},\n", + " {'example_id': '05626-00001',\n", + " 'sentence': \"Comedy troupe Broken Lizard 's first movie is very funny but too concerned with giving us a plot .\",\n", + " 'label': 'neutral',\n", + " 'is_subtree': 0},\n", + " {'example_id': '02940-00001',\n", + " 'sentence': \"Imagine O. Henry 's The Gift of the Magi relocated to the scuzzy underbelly of NYC 's drug scene .\",\n", + " 'label': 'negative',\n", + " 'is_subtree': 0}]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "Here, `score` is one of the labels. `tree` is an NLTK Tree instance. It should render pretty legibly in your browser:" + "train_df.sample(3, random_state=1).to_dict(orient=\"records\")" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", "text/plain": [ - "Tree('3', [Tree('2', [Tree('2', ['The']), Tree('2', ['Rock'])]), Tree('4', [Tree('3', [Tree('2', ['is']), Tree('4', [Tree('2', ['destined']), Tree('2', [Tree('2', [Tree('2', [Tree('2', [Tree('2', ['to']), Tree('2', [Tree('2', ['be']), Tree('2', [Tree('2', ['the']), Tree('2', [Tree('2', ['21st']), Tree('2', [Tree('2', [Tree('2', ['Century']), Tree('2', [\"'s\"])]), Tree('2', [Tree('3', ['new']), Tree('2', [Tree('2', ['``']), Tree('2', ['Conan'])])])])])])])]), Tree('2', [\"''\"])]), Tree('2', ['and'])]), Tree('3', [Tree('2', ['that']), Tree('3', [Tree('2', ['he']), Tree('3', [Tree('2', [\"'s\"]), Tree('3', [Tree('2', ['going']), Tree('3', [Tree('2', ['to']), Tree('4', [Tree('3', [Tree('2', ['make']), Tree('3', [Tree('3', [Tree('2', ['a']), Tree('3', ['splash'])]), Tree('2', [Tree('2', ['even']), Tree('3', ['greater'])])])]), Tree('2', [Tree('2', ['than']), Tree('2', [Tree('2', [Tree('2', [Tree('2', [Tree('1', [Tree('2', ['Arnold']), Tree('2', ['Schwarzenegger'])]), Tree('2', [','])]), Tree('2', [Tree('2', ['Jean-Claud']), Tree('2', [Tree('2', ['Van']), Tree('2', ['Damme'])])])]), Tree('2', ['or'])]), Tree('2', [Tree('2', ['Steven']), Tree('2', ['Segal'])])])])])])])])])])])])]), Tree('2', ['.'])])])" + "8544" ] }, - "execution_count": 5, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "tree" + "train_df.shape[0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "This is what it actually looks like, of course:" + "This yields the following label distribution:" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(Tree('3', [Tree('2', [Tree('2', ['The']), Tree('2', ['Rock'])]), Tree('4', [Tree('3', [Tree('2', ['is']), Tree('4', [Tree('2', ['destined']), Tree('2', [Tree('2', [Tree('2', [Tree('2', [Tree('2', ['to']), Tree('2', [Tree('2', ['be']), Tree('2', [Tree('2', ['the']), Tree('2', [Tree('2', ['21st']), Tree('2', [Tree('2', [Tree('2', ['Century']), Tree('2', [\"'s\"])]), Tree('2', [Tree('3', ['new']), Tree('2', [Tree('2', ['``']), Tree('2', ['Conan'])])])])])])])]), Tree('2', [\"''\"])]), Tree('2', ['and'])]), Tree('3', [Tree('2', ['that']), Tree('3', [Tree('2', ['he']), Tree('3', [Tree('2', [\"'s\"]), Tree('3', [Tree('2', ['going']), Tree('3', [Tree('2', ['to']), Tree('4', [Tree('3', [Tree('2', ['make']), Tree('3', [Tree('3', [Tree('2', ['a']), Tree('3', ['splash'])]), Tree('2', [Tree('2', ['even']), Tree('3', ['greater'])])])]), Tree('2', [Tree('2', ['than']), Tree('2', [Tree('2', [Tree('2', [Tree('2', [Tree('1', [Tree('2', ['Arnold']), Tree('2', ['Schwarzenegger'])]), Tree('2', [','])]), Tree('2', [Tree('2', ['Jean-Claud']), Tree('2', [Tree('2', ['Van']), Tree('2', ['Damme'])])])]), Tree('2', ['or'])]), Tree('2', [Tree('2', ['Steven']), Tree('2', ['Segal'])])])])])])])])])])])])]), Tree('2', ['.'])])]),)" + "positive 3610\n", + "negative 3310\n", + "neutral 1624\n", + "Name: label, dtype: int64" ] }, - "execution_count": 6, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "(tree,)" + "train_df.label.value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Here's a smaller example:" + "You might want to remove the duplicate examples:" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "dup_train_df = sst.train_reader(SST_HOME, dedup=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": "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", "text/plain": [ - "Tree('4', [Tree('2', ['NLU']), Tree('4', [Tree('2', ['is']), Tree('4', ['enlightening'])])])" + "8534" ] }, - "execution_count": 7, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "Tree.fromstring(\"\"\"(4 (2 NLU) (4 (2 is) (4 enlightening)))\"\"\")" + "dup_train_df.shape[0]" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ - "### Methodological notes\n", - "\n", - "* We've deliberately ignored `test` readers. We urge you not to use the `test` set until and unless you are running experiments for a final project or similar. Overuse of test-sets corrupts them, since even subtle lessons learned from those runs can be incorporated back into model-building efforts.\n", - "\n", - "* We actually have mixed feelings about the overuse of `dev` that might result from working with these notebooks! We've tried to encourage using just splits of the training data for assessment most of the time, with only occasionally use of `dev`. This will give you a clearer picture of how you will ultimately do on `test`; over-use of `dev` can lead to over-fitting on that particular dataset with a resulting loss of performance of `test`." + "This removes only one example for this setting so it is unlikely to be a significant choice." ] }, { "cell_type": "markdown", - "metadata": { - "collapsed": true, - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ - "## Modeling the SST labels\n", - "\n", - "Working with the SST involves making decisions about how to handle the raw SST labels. The interpretation of these labels is as follows ([Socher et al., sec. 3](http://www.aclweb.org/anthology/D/D13/D13-1170.pdf)):\n", - "\n", - "* `'0'`: very negative\n", - "* `'1'`: negative\n", - "* `'2'`: neutral\n", - "* `'3'`: positive\n", - "* `'4'`: very positive\n", - "\n", - "The labels look like they could be treated as totally ordered, even continuous. However, conceptually, they do not form such an order. Rather, they consist of three separate classes, with the negative and positive classes being totally ordered in opposite directions:\n", - "\n", - "* `'0' > '1'`: negative\n", - "* `'2'`: neutral\n", - "* `'4' > '3'`: positive\n", - "\n", - "Thus, in this notebook, we'll look mainly at binary (positive/negative) and ternary tasks.\n", + "Our CSV-based distribution should make it easy to do basic analysis of the dataset to inform system development. \n", "\n", - "A related note: the above shows that the __fine-grained sentiment task__ for the SST is particularly punishing as usually formulated, since it ignores the partial-order structure in the categories completely. As a result, mistaking `'0'` for `'1'` is as bad as mistaking `'0'` for `'4'`, though the first error is clearly less severe than the second.\n", - "\n", - "The functions `sst.binary_class_func` and `sst.ternary_class_func` will convert the labels for you, and recommended usage is to use them as the `class_func` keyword argument to `train_reader` and `dev_reader`; examples below." + "Here's a look at the distribution of examples by length in characters:" ] }, { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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tbc/zBHdDhypPr0UsBeYBLwN/Iena0T5SL6x6HSNiE7AJoLe3N/r6+nLFVKlUyNu3SNetfbih61uzcIiNA+UcxqusuRWd18HlfYWtO0u7/DtrtLLmVWu0mfJ+JyJukfTH1PnjHBE3jHObHwUORMT/S7fzIPDvgKOSZkbEEUkzgWNp/0PAnKrPzyY5bWVmZk0y2n9hhi9q72rwNp8HLpJ0MslpqIvTbbwGrAA2pL8fSvtvBf5c0peBdwPzgZ0NjsnMzEYx2kx5/yf9vbmRG4yI76cj2D4ODAF/T3LqaCqwRdJKkoJyTdp/j6QtJGNTDQGrI+KtRsZkZmaja8lJ34i4Gbi5pvkEyVFGvf7r8bDoZmYt4+E+zMwsk4uFmZllyjwNJeldwH8F5lb3n8hzFmZm1lnyXLN4CPgb4LuALyybmXWhPMXi5Ij4YuGRmJlZ28pzzeKbki4rPBIzM2tboz3BfZzkyW0BvyvpBPBmuhwTHabczMw6x2gP5Z3azEDMzKx95Zkpb3ueNjMzK6/RTkOdBJwCzEhHih0e/XUayRhNZmbWJUa7G+q/AZ8jKQyPV7W/CvxJgTGZmVmbGe2axa3ArZKuj4g/bmJMZmbWZvI8Z/GCpKtr2l4BBiLiWL0PmJlZueQpFiuBXwO+ly73ATuAsyT9XkT8WUGxmZlZm8hTLH4O/EpEHAWQ1APcAfwq8CjgYmFmVnJ5nuCeO1woUseAsyLiRZKH9MZM0umSHpD0D5L2Svo1SWdI2ibp2fT39Kr+6yTtl7RP0iXj2aaZmY1fnmLxN5K+KWmFpOHpTh+VdArw8ji3eyvw7Yh4P/BBkilc1wLbI2I+sD1dRtICYBlwDrAEuF3SpHFu18zMxiFPsVgN3A2cB5wP3EMytelrEbF4rBuUNA34CHAnQET8LCJeBpYCw1O4bgauSl8vBfoj4kREHAD2A4vGul0zMxs/RURzNyidRzLn9jMkRxW7gRuBFyLi9Kp+L0XEdEm3ATsi4t60/U7gkYh4oM66VwGrAHp6ei7s7+/PFdPg4CBTp06dSFoNMfDCKw1dX88UOPpGQ1fZNsqaW9F5LZx1WnErz9Au/84arWx5LV68eHdE9Na255n86GrgD4AzSZ7inuhAgm8HLgCuj4jvS7qV9JTTSCHUaatb4SJiE0khore3N/r6+nIFVKlUqO47d+3DuT7XeI2dEn3NwiE2DrRkmvXClTW3ovM6uLyvsHVnqf13VhZlzatWntNQtwBXRsRpETEtIk6d4Iizh4BDEfH9dPkBkuJxVNJMgPT3sar+c6o+Pxs4PIHtm5nZGOUpFkcjYm+jNhgRPwb+SdLZadPFJKektgIr0rbhC+mk7cskTZY0D5gP7GxUPGZmli3P8e4uSV8HvgGcGG6MiAcnsN3rgfskvRP4IfBpksK1RdJK4HngmnQ7eyRtISkoQyQX1z29q5lZE+UpFtOA14GPVbUFMO5iERFPAL90AYXkKKNe//XA+vFuz8zMJiazWETEp5sRiJmZta88d0OdRTK8R09EnCvpAyQXvP9X4dGZWUO16k6/gxsub8l2rXHyXOD+KrCOdGiPiHiK5IlqMzPrEnmKxckRUXv30VARwZiZWXvKUyx+Iul9pA/CSfoEcKTQqMzMrK3kuRtqNclT0e+X9AJwAFheaFRmZtZWMo8sIuKHEfFR4F3A+yPi14HfLDwyMzNrG3lOQwGQjjJ7PF387wXFY2ZmbSh3sahRb3A/MzMrqfEWi+aOa25mZi014gVuScepXxQETCksIjMzazsjFouIOLWZgZiZWfsa72koMzPrIi4WZmaWycXCzMwyuViYmVmmlhULSZMk/b2kb6bLZ0jaJunZ9Pf0qr7rJO2XtE/SJa2K2cysW7XyyOJGoHpu77XA9oiYD2xPl5G0gGRI9HOAJcDtkiY1OVYzs67WkmIhaTZwOfC1qualwOb09Wbgqqr2/og4EREHgP3AoiaFamZmgCKa/zC2pAeA3wdOBb4QER+X9HJEnF7V56WImC7pNmBHRNybtt8JPBIRD9RZ7ypgFUBPT8+F/f39ueIZHBxk6tSp/7I88MIr486tnfRMgaNvtDqKYpQ1t7LmtXDWab/076wsypbX4sWLd0dEb217niHKG0rSx4FjEbFbUl+ej9Rpq1vhImITyXDq9Pb2Rl9fntVDpVKhuu91LZp6stHWLBxi40DTd3FTlDW3suZ1cHnfL/07K4uy5lWrFd/KDwNXSroMOAmYJule4KikmRFxRNJM4Fja/xAwp+rzs4HDTY3YzKzLNf2aRUSsi4jZETGX5ML1/42Ia4GtwIq02wrgofT1VmCZpMmS5gHzgdppXs3MrEDtdLy7AdgiaSXwPHANQETskbQFeIZk7u/VEfFW68I0M+s+LS0WEVEBKunrfwYuHqHfemB90wIzM7Nf4Ce4zcwsk4uFmZllcrEwM7NMLhZmZpbJxcLMzDK5WJiZWSYXCzMzy+RiYWZmmVwszMwsk4uFmZllcrEwM7NMLhZmZpbJxcLMzDK10xDlZlZSc9c+zJqFQ02fhfLghsubur0y85GFmZllanqxkDRH0vck7ZW0R9KNafsZkrZJejb9Pb3qM+sk7Ze0T9IlzY7ZzKzbteLIYghYExG/AlwErJa0AFgLbI+I+cD2dJn0vWXAOcAS4HZJk1oQt5lZ12rFHNxHIuLx9PVxYC8wC1gKbE67bQauSl8vBfoj4kREHAD2A4uaGrSZWZdTRLRu49Jc4FHgXOD5iDi96r2XImK6pNuAHRFxb9p+J/BIRDxQZ32rgFUAPT09F/b39+eKY3BwkKlTp/7L8sALr4w3pbbSMwWOvtHqKIpR1tzKmhe0JreFs04rfBu1fz863eLFi3dHRG9te8vuhpI0FfhL4HMR8aqkEbvWaatb4SJiE7AJoLe3N/r6+nLFUqlUqO7b7Ds2irJm4RAbB8p5w1tZcytrXtCa3A4u7yt8G7V/P8qqJXdDSXoHSaG4LyIeTJuPSpqZvj8TOJa2HwLmVH18NnC4WbGamVlr7oYScCewNyK+XPXWVmBF+noF8FBV+zJJkyXNA+YDO5sVr5mZteY01IeB3wIGJD2Rtv0usAHYImkl8DxwDUBE7JG0BXiG5E6q1RHxVtOjNjPrYk0vFhHxt9S/DgFw8QifWQ+sLywoMzMblZ/gNjOzTC4WZmaWycXCzMwyuViYmVkmFwszM8vkYmFmZpnKOa6AmRnJpEtFG2lSp7JNvOQjCzMzy+RiYWZmmVwszMwsk4uFmZllcrEwM7NMLhZmZpbJxcLMzDK5WJiZWSYXCzMzy9QxT3BLWgLcCkwCvhYRG1ockpnZiJrx9Hg9RT053hFHFpImAX8CXAosAD4paUFrozIz6x4dUSyARcD+iPhhRPwM6AeWtjgmM7OuoYhodQyZJH0CWBIR/yVd/i3gVyPiszX9VgGr0sWzgX05NzED+EmDwm0nZc0LyptbWfOC8uZWtrzeExHvqm3slGsWqtP2S1UuIjYBm8a8cmlXRPSOJ7B2Vta8oLy5lTUvKG9uZc2rVqechjoEzKlang0cblEsZmZdp1OKxQ+A+ZLmSXonsAzY2uKYzMy6RkechoqIIUmfBf6a5NbZuyJiTwM3MeZTVx2irHlBeXMra15Q3tzKmtcv6IgL3GZm1lqdchrKzMxayMXCzMwydXWxkLRE0j5J+yWtbXU8EyXpoKQBSU9I2pW2nSFpm6Rn09/TWx1nFkl3STom6emqthHzkLQu3Yf7JF3SmqjzGSG3L0l6Id1vT0i6rOq9jshN0hxJ35O0V9IeSTem7R2930bJq+P32ZhFRFf+kFwofw54L/BO4ElgQavjmmBOB4EZNW23AGvT12uBP2h1nDny+AhwAfB0Vh4kw788CUwG5qX7dFKrcxhjbl8CvlCnb8fkBswELkhfnwr8Yxp/R++3UfLq+H021p9uPrLoliFElgKb09ebgataF0o+EfEo8GJN80h5LAX6I+JERBwA9pPs27Y0Qm4j6ZjcIuJIRDyevj4O7AVm0eH7bZS8RtIReY1HNxeLWcA/VS0fYvQvQScI4DuSdqdDnwD0RMQRSL74wJkti25iRsqjLPvxs5KeSk9TDZ+q6cjcJM0Fzge+T4n2W01eUKJ9lkc3F4tcQ4h0mA9HxAUko/OulvSRVgfUBGXYj3cA7wPOA44AG9P2jstN0lTgL4HPRcSro3Wt09a2udXJqzT7LK9uLhalG0IkIg6nv48Bf0Vy+HtU0kyA9Pex1kU4ISPl0fH7MSKORsRbEfFz4Kv862mLjspN0jtI/qDeFxEPps0dv9/q5VWWfTYW3VwsSjWEiKRTJJ06/Br4GPA0SU4r0m4rgIdaE+GEjZTHVmCZpMmS5gHzgZ0tiG/chv+Ypn6TZL9BB+UmScCdwN6I+HLVWx2930bKqwz7bMxafYW9lT/AZSR3NzwH3NTqeCaYy3tJ7sJ4EtgznA/wb4DtwLPp7zNaHWuOXO4nObR/k+R/aitHywO4Kd2H+4BLWx3/OHL7M2AAeIrkj83MTssN+HWS0y1PAU+kP5d1+n4bJa+O32dj/fFwH2ZmlqmbT0OZmVlOLhZmZpbJxcLMzDK5WJiZWSYXCzMzy+RiYWZmmVwszMws0/8Hh3wpcvklCRgAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } - }, + ], "source": [ - "### Train label distributions\n", - "\n", - "Check that these numbers all match those reported in [Socher et al. 2013, sec 5.1](http://www.aclweb.org/anthology/D/D13/D13-1170.pdf)." + "_ = train_df.sentence.str.len().hist().set_ylabel(\"Length in characters\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And by word count, assuming a very simple tokenization strategy:" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "train_labels = [y for tree, y in sst.train_reader(SST_HOME)]" + "train_df['word_count'] = train_df.sentence.str.split().apply(len)\n", + "\n", + "_ = train_df['word_count'].hist().set_ylabel(\"Length in words\")" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 13, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total train examples: 8,544\n" - ] + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "print(\"Total train examples: {:,}\".format(len(train_labels)))" + "_ = train_df.boxplot(\"word_count\", by=\"label\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Including subtrees" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Distribution over the full label set:" + "Much of the special interest of the SST is that it includes labels, not just for full examples, but also for all the constituent words and phrases in those examples. You might also want to try training on this expanded dataset. It's much larger and so experiments will be more costly in terms of time and compute resources, but it could be worth it." ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "subtree_train_df = sst.train_reader(SST_HOME, include_subtrees=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "3 2322\n", - "1 2218\n", - "2 1624\n", - "4 1288\n", - "0 1092\n", - "dtype: int64" + "318582" ] }, - "execution_count": 10, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.Series(train_labels).value_counts()" + "subtree_train_df.shape[0]" ] }, { - "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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example_idsentencelabelis_subtree
000001-00001The Rock is destined to be the 21st Century 's...positive0
100001-00002The Rockneutral1
200001-00003Theneutral1
300001-00004Rockneutral1
400001-00005is destined to be the 21st Century 's new `` C...positive1
\n", + "
" + ], + "text/plain": [ + " example_id sentence label \\\n", + "0 00001-00001 The Rock is destined to be the 21st Century 's... positive \n", + "1 00001-00002 The Rock neutral \n", + "2 00001-00003 The neutral \n", + "3 00001-00004 Rock neutral \n", + "4 00001-00005 is destined to be the 21st Century 's new `` C... positive \n", + "\n", + " is_subtree \n", + "0 0 \n", + "1 1 \n", + "2 1 \n", + "3 1 \n", + "4 1 " + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" } - }, + ], "source": [ - "Binary label conversion:" + "subtree_train_df.head()" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "subtree_train_df['word_count'] = subtree_train_df.sentence.str.split().apply(len)\n", + "\n", + "_ = subtree_train_df['word_count'].hist().set_ylabel(\"Length in words\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this setting, removing duplicates has a large effect, since many subtrees are repeated:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ - "binary_train_labels = [\n", - " y for tree, y in sst.train_reader(SST_HOME, class_func=sst.binary_class_func)]" + "subtree_dedup_train_df = sst.train_reader(SST_HOME, include_subtrees=True, dedup=True)" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 19, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total binary train examples: 6,920\n" - ] + "data": { + "text/plain": [ + "(159274, 4)" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "print(\"Total binary train examples: {:,}\".format(len(binary_train_labels)))" + "subtree_dedup_train_df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Label distribution:" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "positive 3610\n", - "negative 3310\n", - "dtype: int64" + "neutral 81658\n", + "positive 42672\n", + "negative 34944\n", + "Name: label, dtype: int64" ] }, - "execution_count": 13, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.Series(binary_train_labels).value_counts()" + "subtree_dedup_train_df.label.value_counts()" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, + "source": [ + "### Dev and test splits" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ - "Ternary label conversion:" + "For the dev and test splits, we include only the root-level examples, and we do not deduplicate to remain aligned with the original paper. (The dev set has one repeated example, and the test set has none.)" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "dev_df = sst.dev_reader(SST_HOME)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "positive 3610\n", - "negative 3310\n", - "neutral 1624\n", - "dtype: int64" + "(1101, 4)" ] }, - "execution_count": 14, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ternary_train_labels = [\n", - " y for tree, y in sst.train_reader(SST_HOME, class_func=sst.ternary_class_func)]\n", - "\n", - "pd.Series(ternary_train_labels).value_counts()" + "dev_df.shape" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" + "metadata": {}, + "source": [ + "Label distribution:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "positive 444\n", + "negative 428\n", + "neutral 229\n", + "Name: label, dtype: int64" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" } - }, + ], + "source": [ + "dev_df.label.value_counts()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ - "### Dev label distributions\n", + "There is an associated `sst.test_reader(SST_HOME)` with 2,210 (root-only) examples and no duplicates. As always in our field, you should use the test set only at the very end of your system development, and you should never, ever develop a system on the basis of test-set scores. \n", + "\n", + "In a similar vein, you should use the dev set only very sparingly. This will give you a clearer picture of how you will ultimately do on test; over-use of a dev set can lead to over-fitting on that particular dataset with a resulting loss of performance at test time.\n", "\n", - "Check that these numbers all match those reported in [Socher et al. 2013, sec 5.1](http://www.aclweb.org/anthology/D/D13/D13-1170.pdf)." + "In the homework and associated bake-off for this course, we will introduce a second dev/test pair involving sentences about restaurants. The goal there is to have a fresh test set, and to push you to develop a system that works both for the SST movie domain and this new domain." ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ - "dev_labels = [y for tree, y in sst.dev_reader(SST_HOME)]" + "_ = dev_df.sentence.str.len().hist().set_ylabel(\"Length in characters\")" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 25, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total dev examples: 1,101\n" - ] + "data": { + "image/png": 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fVNX/SvIl4KYkbwPuB97YQ22SNNHGHgpVdR/w0gXa/x/w6nHXI0l6ykr6SqokqWeGgiSpZShIklqGgiSpZShIklqTPdNH0jHV14TQlTBpbq3wSEGS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEktQ0GS1DIUJEmtZ/VdgCQt1/Tm29rlTesPcuXQ+ijt3XLJWLYzTh4pSJJahoIkqWUoSJJahoIkqWUoSJJahoIkqWUoSJJahoIkqWUoSJJazmiWpCWaHtPM6YWMajb1ijtSSHJxknuS7Emyue96JGmSrKhQSHIc8KfAfwDOB96c5Px+q5KkybGiQgF4GbCnqu6rqu8D24FLe65JkiZGqqrvGlpJfhG4uKp+tVn/ZeDlVfX2oedsBDY2qz8O3NMsnwZ8a4zlrjSTvv9gH4B9APZBl/3/0ao6faEHVtqJ5izQ9rTUqqqtwNZnvDDZWVUzoypspZv0/Qf7AOwDsA+Wu/8rbfjoAeCcofWzgYd6qkWSJs5KC4UvAeclOTfJvwAuB27puSZJmhgravioqg4meTvwl8BxwI1VdVfHlz9jSGnCTPr+g30A9gHYB8va/xV1olmS1K+VNnwkSeqRoSBJaq36UJjEy2IkuTHJ/iR3DrWdmuT2JPc2v0/ps8ZRSnJOks8luTvJXUmubtonqQ+em+SLSf6h6YM/aNonpg/mJTkuyVeS3NqsT1QfJNmbZHeSrybZ2bQtuQ9WdShM8GUxPghcfEjbZmBHVZ0H7GjW16qDwKaqehHwCuCq5s99kvrgCeCnq+qlwIXAxUlewWT1wbyrgbuH1iexDzZU1YVD8xOW3AerOhSY0MtiVNUdwLcPab4U2NYsbwNeP86axqmqHq6qLzfLjzP4QDiLyeqDqqoDzeqzm59igvoAIMnZwCXAfxtqnqg+WMSS+2C1h8JZwP8ZWn+gaZtEU1X1MAw+NIEzeq5nLJJMA/8G+HsmrA+aYZOvAvuB26tq4voA+GPgd4EfDLVNWh8U8Nkku5rLAMEy+mBFzVNYgiNeFkNrV5J1wCeA36qqx5KF/jqsXVX1JHBhkpOBTyW5oOeSxirJzwL7q2pXktmey+nTK6vqoSRnALcn+cZy3my1Hyl4WYyn7EtyJkDze3/P9YxUkmczCIQPV9Unm+aJ6oN5VfUdYI7BeaZJ6oNXAj+fZC+DoeOfTvIhJqsPqKqHmt/7gU8xGFZfch+s9lDwshhPuQW4olm+Ari5x1pGKoNDghuAu6vqvUMPTVIfnN4cIZDkeOBngG8wQX1QVddU1dlVNc3g3/5fV9UvMUF9kOSEJCfOLwOvAe5kGX2w6mc0J3kdg3HF+ctiXNtvRaOX5CPALINL5O4D3gl8GrgJ+FfA/cAbq+rQk9FrQpJXAZ8HdvPUWPI7GJxXmJQ+eAmDE4jHMfjP3U1V9e4kP8KE9MGwZvjod6rqZyepD5L8GIOjAxicDviLqrp2OX2w6kNBknTsrPbhI0nSMWQoSJJahoIkqWUoSJJahoIkqWUoSJJahoIkqfXPqcrNUmBi8m4AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "print(\"Total dev examples: {:,}\".format(len(dev_labels)))" + "dev_df['word_count'] = dev_df.sentence.str.split().apply(len)\n", + "\n", + "_ = dev_df['word_count'].hist().set_ylabel(\"Length in words\")" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { + "image/png": "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\n", "text/plain": [ - "1 289\n", - "3 279\n", - "2 229\n", - "4 165\n", - "0 139\n", - "dtype: int64" + "
" ] }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "pd.Series(dev_labels).value_counts()" + "_ = dev_df.boxplot(\"word_count\", by=\"label\")" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, "source": [ - "Binary label conversion:" + "## Tokenization" ] }, { - "cell_type": "code", - "execution_count": 18, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "binary_dev_labels = [\n", - " y for tree, y in sst.dev_reader(SST_HOME, class_func=sst.binary_class_func)]" + "The SST began as a collection of sentences from [Rotten Tomatoes](https://www.rottentomatoes.com/) that were released as a corpus by [Pang and Lee 2004](https://doi.org/10.3115/1218955.1218990). The data were parsed as part of the SST project, and we are now releasing them in a flat format similar to what one sees in benchmarks like [GLUE](https://gluebenchmark.com). Along this journey, the sentences have acquired a tokenization scheme that is reminiscent of what one sees in standard [Penn Treenbank](https://catalog.ldc.upenn.edu/docs/LDC95T7/cl93.html) formats, with some additional quirks. This makes the tokens different in sigificant respects from what one sees in most standard English texts:" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 27, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Total binary dev examples: 872\n" - ] + "data": { + "text/plain": [ + "\"The Rock is destined to be the 21st Century 's new `` Conan '' and that he 's going to make a splash even greater than Arnold Schwarzenegger , Jean-Claud Van Damme or Steven Segal .\"" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "print(\"Total binary dev examples: {:,}\".format(len(binary_dev_labels)))" + "ex = train_df.iloc[0].sentence\n", + "\n", + "ex" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "One can address some of this using the NLTK `TreebankWordDetokenizer`:" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "detokenizer = TreebankWordDetokenizer()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "def detokenize(s):\n", + " return detokenizer.detokenize(s.split())" + ] + }, + { + "cell_type": "code", + "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "positive 444\n", - "negative 428\n", - "dtype: int64" + "'The Rock is destined to be the 21st Century\\'s new``Conan\"and that he\\'s going to make a splash even greater than Arnold Schwarzenegger, Jean-Claud Van Damme or Steven Segal.'" ] }, - "execution_count": 20, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pd.Series(binary_dev_labels).value_counts()" + "detokenize(ex)" ] }, { "cell_type": "markdown", - "metadata": { - "slideshow": { - "slide_type": "slide" - } - }, + "metadata": {}, + "source": [ + "As you can see, there is additional clean-up one could do, but this is a start." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [ - "Ternary label conversion:" + "Another option would be to go in the reverse – for outside data, one could try to bring it into the SST format:" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "tokenizer = TreebankWordTokenizer()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "def treebank_tokenize(s):\n", + " return tokenizer.tokenize(s)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "positive 444\n", - "negative 428\n", - "neutral 229\n", - "dtype: int64" + "['The',\n", + " 'Rock',\n", + " 'is',\n", + " \"n't\",\n", + " 'the',\n", + " 'new',\n", + " '``',\n", + " 'Conan',\n", + " \"''\",\n", + " '–',\n", + " 'he',\n", + " \"'s\",\n", + " 'this',\n", + " 'generation',\n", + " \"'s\",\n", + " 'Olivier',\n", + " '!']" ] }, - "execution_count": 21, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "ternary_dev_labels = [\n", - " y for tree, y in sst.dev_reader(SST_HOME, class_func=sst.ternary_class_func)]\n", - "\n", - "pd.Series(ternary_dev_labels).value_counts()" + "treebank_tokenize(\"The Rock isn't the new ``Conan'' – he's this generation's Olivier!\")" ] } ], @@ -676,7 +916,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -684,5 +924,5 @@ } }, "nbformat": 4, - "nbformat_minor": 1 + "nbformat_minor": 4 } diff --git a/sst_02_hand_built_features.ipynb b/sst_02_hand_built_features.ipynb index 94183e7..96747c6 100644 --- a/sst_02_hand_built_features.ipynb +++ b/sst_02_hand_built_features.ipynb @@ -13,12 +13,12 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -94,19 +94,20 @@ "outputs": [], "source": [ "from collections import Counter\n", - "from np_sgd_classifier import BasicSGDClassifier\n", "import os\n", "import pandas as pd\n", "from sklearn.feature_extraction import DictVectorizer\n", "from sklearn.feature_extraction.text import TfidfTransformer\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import classification_report\n", + "from sklearn.model_selection import PredefinedSplit\n", "from sklearn.naive_bayes import MultinomialNB\n", "from sklearn.pipeline import Pipeline\n", "from sklearn.svm import LinearSVC\n", "import scipy.stats\n", - "from nltk.tree import Tree\n", "import torch.nn as nn\n", + "\n", + "from np_sgd_classifier import BasicSGDClassifier\n", "from torch_shallow_neural_classifier import TorchShallowNeuralClassifier\n", "import sst\n", "import utils" @@ -127,7 +128,7 @@ "metadata": {}, "outputs": [], "source": [ - "SST_HOME = os.path.join('data', 'trees')" + "SST_HOME = os.path.join('data', 'sentiment')" ] }, { @@ -173,14 +174,14 @@ "metadata": {}, "outputs": [], "source": [ - "def unigrams_phi(tree):\n", + "def unigrams_phi(text):\n", " \"\"\"\n", " The basis for a unigrams feature function. Downcases all tokens.\n", "\n", " Parameters\n", " ----------\n", - " tree : nltk.tree\n", - " The tree to represent.\n", + " text : str\n", + " The example to represent.\n", "\n", " Returns\n", " -------\n", @@ -189,7 +190,7 @@ " list to a dict of counts of the elements in that list.)\n", "\n", " \"\"\"\n", - " return Counter([w.lower() for w in tree.leaves()])" + " return Counter(text.lower().split())" ] }, { @@ -198,7 +199,7 @@ "metadata": {}, "outputs": [], "source": [ - "example_tree = Tree.fromstring(\"\"\"(4 (2 NLU) (4 (2 is) (4 enlightening)))\"\"\")" + "example_text = \"NLU is enlightening !\"" ] }, { @@ -209,7 +210,7 @@ { "data": { "text/plain": [ - "Counter({'nlu': 1, 'is': 1, 'enlightening': 1})" + "Counter({'nlu': 1, 'is': 1, 'enlightening': 1, '!': 1})" ] }, "execution_count": 7, @@ -218,7 +219,7 @@ } ], "source": [ - "unigrams_phi(example_tree)" + "unigrams_phi(example_text)" ] }, { @@ -234,24 +235,24 @@ "metadata": {}, "outputs": [], "source": [ - "def bigrams_phi(tree):\n", + "def bigrams_phi(text):\n", " \"\"\"\n", " The basis for a bigrams feature function. Downcases all tokens.\n", "\n", " Parameters\n", " ----------\n", - " tree : nltk.tree\n", - " The tree to represent.\n", + " text : str\n", + " The example to represent.\n", "\n", " Returns\n", " -------\n", " defaultdict\n", - " A map from tuples to their counts in `tree`.\n", + " A map from tuples to their counts in `text`.\n", "\n", " \"\"\"\n", - " leaves = [w.lower() for w in tree.leaves()]\n", - " left = [utils.START_SYMBOL] + leaves\n", - " right = leaves + [utils.END_SYMBOL]\n", + " toks = text.lower().split()\n", + " left = [utils.START_SYMBOL] + toks\n", + " right = toks + [utils.END_SYMBOL]\n", " grams = list(zip(left, right))\n", " return Counter(grams)" ] @@ -267,7 +268,8 @@ "Counter({('', 'nlu'): 1,\n", " ('nlu', 'is'): 1,\n", " ('is', 'enlightening'): 1,\n", - " ('enlightening', ''): 1})" + " ('enlightening', '!'): 1,\n", + " ('!', ''): 1})" ] }, "execution_count": 9, @@ -276,7 +278,7 @@ } ], "source": [ - "bigrams_phi(example_tree)" + "bigrams_phi(example_text)" ] }, { @@ -385,13 +387,13 @@ " \n", " \n", " \n", - " 0\n", + " 0\n", " 1.0\n", " 1.0\n", " 0.0\n", " \n", " \n", - " 1\n", + " 1\n", " 0.0\n", " 1.0\n", " 2.0\n", @@ -489,13 +491,13 @@ " \n", " \n", " \n", - " 0\n", + " 0\n", " 2.0\n", " 0.0\n", " 1.0\n", " \n", " \n", - " 1\n", + " 1\n", " 4.0\n", " 2.0\n", " 0.0\n", @@ -583,9 +585,8 @@ "\n", "The second major phase for our analysis is a kind of set-up phase. Ingredients:\n", "\n", - "* A reader like `train_reader`\n", + "* A dataset from a function like `sst.train_reader`\n", "* A feature function like `unigrams_phi`\n", - "* A class function like `binary_class_func`\n", "\n", "The convenience function `sst.build_dataset` uses these to build a dataset for training and assessing a model. See its documentation for details on how it works. Much of this is about taking advantage of `sklearn`'s many functions for model building." ] @@ -597,10 +598,8 @@ "outputs": [], "source": [ "train_dataset = sst.build_dataset(\n", - " SST_HOME,\n", - " reader=sst.train_reader,\n", + " sst.train_reader(SST_HOME),\n", " phi=unigrams_phi,\n", - " class_func=sst.binary_class_func,\n", " vectorizer=None)" ] }, @@ -613,7 +612,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Train dataset with unigram features has 6,920 examples and 14,828 features.\n" + "Train dataset with unigram features has 8,544 examples and 16,579 features.\n" ] } ], @@ -640,10 +639,8 @@ "outputs": [], "source": [ "dev_dataset = sst.build_dataset(\n", - " SST_HOME,\n", - " reader=sst.dev_reader,\n", + " sst.dev_reader(SST_HOME),\n", " phi=unigrams_phi,\n", - " class_func=sst.binary_class_func,\n", " vectorizer=train_dataset['vectorizer'])" ] }, @@ -656,7 +653,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Dev dataset with unigram features has 872 examples and 14,828 features\n" + "Dev dataset with unigram features has 1,101 examples and 16,579 features\n" ] } ], @@ -781,25 +778,24 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.725 0.780 0.752 941\n", - " positive 0.805 0.755 0.779 1135\n", + " negative 0.660 0.526 0.585 428\n", + " neutral 0.261 0.258 0.259 229\n", + " positive 0.612 0.736 0.669 444\n", "\n", - " accuracy 0.766 2076\n", - " macro avg 0.765 0.768 0.766 2076\n", - "weighted avg 0.769 0.766 0.767 2076\n", + " accuracy 0.555 1101\n", + " macro avg 0.511 0.507 0.504 1101\n", + "weighted avg 0.558 0.555 0.551 1101\n", "\n" ] } ], "source": [ "_ = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_basic_sgd_classifier,\n", - " train_reader=sst.train_reader,\n", - " assess_reader=None,\n", + " assess_dataframes=sst.dev_reader(SST_HOME),\n", " train_size=0.7,\n", - " class_func=sst.binary_class_func,\n", " score_func=utils.safe_macro_f1,\n", " verbose=True)" ] @@ -810,7 +806,7 @@ "source": [ "A few notes on this function call:\n", " \n", - "* Since `assess_reader=None`, the function reports performance on a random train–test split from `train_reader`. Give `sst.dev_reader` as the argument to assess against the `dev` set.\n", + "* Since `assess_dataframes=None`, the function reports performance on a random train–test split from `train_dataframes`, as given by the first argument. Give `sst.dev_reader(SST_HOME)` as the argument to assess against the `dev` set.\n", "\n", "* `unigrams_phi` is the function we defined above. By changing/expanding this function, you can start to improve on the above baseline, perhaps periodically seeing how you do on the dev set.\n", "\n", @@ -884,19 +880,20 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.756 0.745 0.751 973\n", - " positive 0.778 0.788 0.783 1103\n", + " negative 0.628 0.689 0.657 996\n", + " neutral 0.336 0.157 0.214 479\n", + " positive 0.671 0.770 0.717 1089\n", "\n", - " accuracy 0.768 2076\n", - " macro avg 0.767 0.766 0.767 2076\n", - "weighted avg 0.768 0.768 0.768 2076\n", + " accuracy 0.624 2564\n", + " macro avg 0.545 0.538 0.529 2564\n", + "weighted avg 0.592 0.624 0.600 2564\n", "\n" ] } ], "source": [ "_ = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_softmax_classifier)" ] @@ -968,7 +965,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 26. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.20748527348041534" + "Stopping after epoch 23. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.7719634175300598" ] }, { @@ -977,19 +974,20 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.791 0.720 0.754 1011\n", - " positive 0.755 0.820 0.786 1065\n", + " negative 0.627 0.714 0.668 977\n", + " neutral 0.321 0.105 0.158 497\n", + " positive 0.659 0.779 0.714 1090\n", "\n", - " accuracy 0.771 2076\n", - " macro avg 0.773 0.770 0.770 2076\n", - "weighted avg 0.773 0.771 0.770 2076\n", + " accuracy 0.624 2564\n", + " macro avg 0.536 0.533 0.513 2564\n", + "weighted avg 0.581 0.624 0.589 2564\n", "\n" ] } ], "source": [ "_ = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_nn_classifier)" ] @@ -1047,7 +1045,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 658. Training loss did not improve more than tol=1e-05. Final error is 0.44765447825193405." + "Stopping after epoch 609. Training loss did not improve more than tol=1e-05. Final error is 1.1642730385065079." ] }, { @@ -1056,19 +1054,20 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.774 0.747 0.761 997\n", - " positive 0.774 0.799 0.786 1079\n", + " negative 0.633 0.691 0.661 969\n", + " neutral 0.317 0.174 0.225 528\n", + " positive 0.661 0.753 0.704 1067\n", "\n", - " accuracy 0.774 2076\n", - " macro avg 0.774 0.773 0.773 2076\n", - "weighted avg 0.774 0.774 0.774 2076\n", + " accuracy 0.610 2564\n", + " macro avg 0.537 0.539 0.530 2564\n", + "weighted avg 0.579 0.610 0.589 2564\n", "\n" ] } ], "source": [ "_ = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_torch_softmax)" ] @@ -1109,19 +1108,20 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.753 0.767 0.760 936\n", - " positive 0.806 0.793 0.799 1140\n", + " negative 0.611 0.726 0.664 965\n", + " neutral 0.361 0.051 0.089 511\n", + " positive 0.646 0.798 0.714 1088\n", "\n", - " accuracy 0.781 2076\n", - " macro avg 0.779 0.780 0.780 2076\n", - "weighted avg 0.782 0.781 0.781 2076\n", + " accuracy 0.622 2564\n", + " macro avg 0.539 0.525 0.489 2564\n", + "weighted avg 0.576 0.622 0.570 2564\n", "\n" ] } ], "source": [ "_ = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_pipeline_softmax)" ] @@ -1161,7 +1161,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 43. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.360526978969574" + "Stopping after epoch 13. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 4.746284365653992" ] }, { @@ -1170,19 +1170,20 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.771 0.753 0.762 985\n", - " positive 0.782 0.798 0.790 1091\n", + " negative 0.588 0.700 0.639 997\n", + " neutral 0.239 0.274 0.256 456\n", + " positive 0.740 0.569 0.643 1111\n", "\n", - " accuracy 0.777 2076\n", - " macro avg 0.777 0.776 0.776 2076\n", - "weighted avg 0.777 0.777 0.777 2076\n", + " accuracy 0.567 2564\n", + " macro avg 0.522 0.514 0.513 2564\n", + "weighted avg 0.592 0.567 0.573 2564\n", "\n" ] } ], "source": [ "_ = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_pipeline_classifier)" ] @@ -1296,27 +1297,27 @@ "name": "stdout", "output_type": "stream", "text": [ - "Best params: {'C': 2.0, 'class_weight': None, 'penalty': 'l2'}\n", - "Best score: 0.784\n", + "Best params: {'C': 1.0, 'class_weight': 'balanced', 'penalty': 'l2'}\n", + "Best score: 0.541\n", " precision recall f1-score support\n", "\n", - " negative 0.781 0.743 0.762 428\n", - " positive 0.763 0.800 0.781 444\n", + " negative 0.635 0.659 0.647 428\n", + " neutral 0.313 0.223 0.260 229\n", + " positive 0.652 0.725 0.687 444\n", "\n", - " accuracy 0.772 872\n", - " macro avg 0.772 0.771 0.771 872\n", - "weighted avg 0.772 0.772 0.772 872\n", + " accuracy 0.595 1101\n", + " macro avg 0.533 0.536 0.531 1101\n", + "weighted avg 0.575 0.595 0.582 1101\n", "\n" ] } ], "source": [ "softmax_experiment = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_softmax_with_hyperparameter_search,\n", - " class_func=sst.binary_class_func,\n", - " assess_reader=sst.dev_reader)" + " assess_dataframes=sst.dev_reader(SST_HOME))" ] }, { @@ -1341,6 +1342,74 @@ "| SVM | 79.4 |" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The following reduces the dataset to the binary task:" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "train_df = sst.train_reader(SST_HOME)\n", + "\n", + "train_bin_df = train_df[train_df.label != 'neutral']" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "dev_df = sst.dev_reader(SST_HOME)\n", + "\n", + "dev_bin_df = dev_df[dev_df.label != 'neutral']" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "test_df = sst.sentiment_reader(os.path.join(SST_HOME, \"sst3-test-labeled.csv\"))\n", + "\n", + "test_bin_df = test_df[test_df.label != 'neutral']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note: we will continue to train on just the full examples, so that the experiments do not require a lot of time and computational resources. However, there are probably gains to be had from training on the subtrees as well. In that case, one needs to be careful in cross-validation: the test set needs to be the root-only dev set rather than slices of the train set. To achieve this, one can use a `PredefinedSplit`:" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [], + "source": [ + "full_train_df = sst.train_reader(SST_HOME, include_subtrees=True)\n", + "full_train_bin_df = full_train_df[full_train_df.label != 'neutral']\n", + "\n", + "split_indices = [0] * full_train_bin_df.shape[0]\n", + "split_indices += [-1] * dev_bin_df.shape[0]\n", + "sst_train_dev_splitter = PredefinedSplit(split_indices)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This would be used in place of `cv=5` in the model wrappers below." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1352,7 +1421,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -1364,7 +1433,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -1385,23 +1454,22 @@ ], "source": [ "_ = sst.experiment(\n", - " SST_HOME,\n", + " train_bin_df,\n", " unigrams_phi,\n", " fit_unigram_nb_classifier,\n", - " class_func=sst.binary_class_func,\n", - " assess_reader=sst.dev_reader)" + " assess_dataframes=dev_bin_df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "This falls short of our goal by almost two percentage points, which is not encouraging about how we would do on the test set. However, `MultinomialNB` has a regularization term `alpha` that might have a significant impact given the very large, sparse feature matrices we are creating with `unigrams_phi`. In addition, it might help to transform the raw feature counts, for the same reason that reweighting was so powerful in our VSM module. The best way to try out all these ideas is to do a wide hyperparameter search. The following model wrapper function implements these steps: " + "This falls slightly short of our goal, which is not encouraging about how we would do on the test set. However, `MultinomialNB` has a regularization term `alpha` that might have a significant impact given the very large, sparse feature matrices we are creating with `unigrams_phi`. In addition, it might help to transform the raw feature counts, for the same reason that reweighting was so powerful in our VSM module. The best way to try out all these ideas is to do a wide hyperparameter search. The following model wrapper function implements these steps: " ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ @@ -1412,7 +1480,7 @@ " pipeline = Pipeline([('scaler', rescaler), ('model', mod)])\n", "\n", " # Access the alpha and fit_prior parameters of `mod` with\n", - " # `mod__alpha` and `model__fit_prior`, where \"model\" is the\n", + " # `model__alpha` and `model__fit_prior`, where \"model\" is the\n", " # name from the Pipeline. Use 'passthrough' to optionally\n", " # skip TF-IDF.\n", " param_grid = {\n", @@ -1421,7 +1489,9 @@ " 'model__alpha': [0.1, 0.2, 0.4, 0.8, 1.0, 1.2]}\n", "\n", " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", - " X, y, pipeline, param_grid=param_grid, cv=5)\n", + " X, y, pipeline,\n", + " param_grid=param_grid,\n", + " cv=5)\n", " return bestmod" ] }, @@ -1434,7 +1504,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 44, "metadata": {}, "outputs": [ { @@ -1442,56 +1512,7 @@ "output_type": "stream", "text": [ "Best params: {'model__alpha': 1.2, 'model__fit_prior': False, 'scaler': TfidfTransformer()}\n", - "Best score: 0.790\n", - " precision recall f1-score support\n", - "\n", - " negative 0.807 0.775 0.791 1108\n", - " positive 0.805 0.833 0.819 1230\n", - "\n", - " accuracy 0.806 2338\n", - " macro avg 0.806 0.804 0.805 2338\n", - "weighted avg 0.806 0.806 0.806 2338\n", - "\n" - ] - } - ], - "source": [ - "unigram_nb_experiment_xval = sst.experiment(\n", - " SST_HOME,\n", - " unigrams_phi,\n", - " fit_nb_classifier_with_hyperparameter_search,\n", - " class_func=sst.binary_class_func,\n", - " train_reader=(sst.train_reader, sst.dev_reader))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "At this point, we can create a new model with the parameters we found above, and train it on the combination of the train and dev datasets, on the assumption that this extra training data might be useful:" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_optimized_unigram_nb_classifier(X, y):\n", - " pipeline = unigram_nb_experiment_xval['model']\n", - " pipeline.fit(X, y)\n", - " return pipeline" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Best score: 0.798\n", " precision recall f1-score support\n", "\n", " negative 0.852 0.798 0.824 912\n", @@ -1505,20 +1526,18 @@ } ], "source": [ - "unigram_nb_experiment = sst.experiment(\n", - " SST_HOME,\n", + "unigram_nb_experiment_xval = sst.experiment(\n", + " [train_bin_df, dev_bin_df],\n", " unigrams_phi,\n", - " fit_optimized_unigram_nb_classifier,\n", - " class_func=sst.binary_class_func,\n", - " train_reader=(sst.train_reader, sst.dev_reader),\n", - " assess_reader=sst.test_reader)" + " fit_nb_classifier_with_hyperparameter_search,\n", + " assess_dataframes=test_bin_df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "We're right around the target of 81.8, so we can say that we reproduced the paper's result." + "We're above the target of 81.8, so we can say that we reproduced the paper's result." ] }, { @@ -1530,57 +1549,6 @@ "For the bigram NaiveBayes mode, we can continue to use `fit_nb_classifier_with_hyperparameter_search`, but now the experiment is done with `bigrams_phi`:" ] }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best params: {'model__alpha': 0.2, 'model__fit_prior': False, 'scaler': TfidfTransformer()}\n", - "Best score: 0.736\n", - " precision recall f1-score support\n", - "\n", - " negative 0.722 0.804 0.761 1118\n", - " positive 0.800 0.716 0.756 1220\n", - "\n", - " accuracy 0.758 2338\n", - " macro avg 0.761 0.760 0.758 2338\n", - "weighted avg 0.763 0.758 0.758 2338\n", - "\n" - ] - } - ], - "source": [ - "bigram_nb_experiment_xval = sst.experiment(\n", - " SST_HOME,\n", - " bigrams_phi,\n", - " fit_nb_classifier_with_hyperparameter_search,\n", - " class_func=sst.binary_class_func,\n", - " train_reader=(sst.train_reader, sst.dev_reader))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For our evaluation, we'll train a new model on the union of the train and dev sets, using the best parameters from `bigram_nb_experiment_xval`:" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_optimized_bigram_nb_classifier(X, y):\n", - " pipeline = bigram_nb_experiment_xval['model']\n", - " pipeline.fit(X, y)\n", - " return pipeline" - ] - }, { "cell_type": "code", "execution_count": 45, @@ -1590,6 +1558,8 @@ "name": "stdout", "output_type": "stream", "text": [ + "Best params: {'model__alpha': 0.2, 'model__fit_prior': False, 'scaler': TfidfTransformer()}\n", + "Best score: 0.764\n", " precision recall f1-score support\n", "\n", " negative 0.796 0.754 0.775 912\n", @@ -1603,13 +1573,11 @@ } ], "source": [ - "bigram_nb_experiment = sst.experiment(\n", - " SST_HOME,\n", + "bigram_nb_experiment_xval = sst.experiment(\n", + " [train_bin_df, dev_bin_df],\n", " bigrams_phi,\n", - " fit_optimized_bigram_nb_classifier,\n", - " class_func=sst.binary_class_func,\n", - " train_reader=(sst.train_reader, sst.dev_reader),\n", - " assess_reader=sst.test_reader)" + " fit_nb_classifier_with_hyperparameter_search,\n", + " assess_dataframes=test_bin_df)" ] }, { @@ -1646,7 +1614,9 @@ " 'model__C': [0.1, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4]}\n", "\n", " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", - " X, y, pipeline, param_grid=param_grid, cv=5)\n", + " X, y, pipeline,\n", + " param_grid=param_grid,\n", + " cv=5)\n", " return bestmod" ] }, @@ -1660,56 +1630,7 @@ "output_type": "stream", "text": [ "Best params: {'model__C': 0.4, 'scaler': TfidfTransformer()}\n", - "Best score: 0.787\n", - " precision recall f1-score support\n", - "\n", - " negative 0.801 0.771 0.786 428\n", - " positive 0.787 0.815 0.801 444\n", - "\n", - " accuracy 0.794 872\n", - " macro avg 0.794 0.793 0.793 872\n", - "weighted avg 0.794 0.794 0.793 872\n", - "\n" - ] - } - ], - "source": [ - "svm_experiment_xval = sst.experiment(\n", - " SST_HOME,\n", - " unigrams_phi,\n", - " fit_svm_classifier_with_hyperparameter_search,\n", - " class_func=sst.binary_class_func,\n", - " assess_reader=sst.dev_reader)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This dev set number is not very encouraging, but we've seen that the test set might actually be a bit easier, so we press on with the planned test set evaluation:" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_optimized_svm_classifier(X, y):\n", - " pipeline = svm_experiment_xval['model']\n", - " pipeline.fit(X, y)\n", - " return pipeline" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Best score: 0.797\n", " precision recall f1-score support\n", "\n", " negative 0.844 0.795 0.819 912\n", @@ -1723,13 +1644,11 @@ } ], "source": [ - "svm_experiment = sst.experiment(\n", - " SST_HOME,\n", + "svm_experiment_xval = sst.experiment(\n", + " [train_bin_df, dev_bin_df],\n", " unigrams_phi,\n", - " fit_optimized_svm_classifier,\n", - " class_func=sst.binary_class_func,\n", - " train_reader=(sst.train_reader, sst.dev_reader),\n", - " assess_reader=sst.test_reader)" + " fit_svm_classifier_with_hyperparameter_search,\n", + " assess_dataframes=test_bin_df)" ] }, { @@ -1775,31 +1694,29 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 48, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Model 1 mean: 0.780\n", - "Model 2 mean: 0.749\n", - "p = 0.005\n" + "Model 1 mean: 0.522\n", + "Model 2 mean: 0.509\n", + "p = 0.014\n" ] } ], "source": [ "_ = sst.compare_models(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " unigrams_phi,\n", " fit_softmax_classifier,\n", " stats_test=scipy.stats.wilcoxon,\n", " trials=10,\n", - " phi2=None, # Defaults to same as first required argument.\n", - " train_func2=fit_basic_sgd_classifier, # Defaults to same as second required argument.\n", - " reader=sst.train_reader,\n", + " phi2=None, # Defaults to same as first argument.\n", + " train_func2=fit_basic_sgd_classifier, # Defaults to same as second argument.\n", " train_size=0.7,\n", - " class_func=sst.binary_class_func,\n", " score_func=utils.safe_macro_f1)" ] }, @@ -1818,19 +1735,19 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 50, "metadata": {}, "outputs": [], "source": [ "m = utils.mcnemar(\n", - " unigram_nb_experiment['assess_dataset']['y'],\n", - " unigram_nb_experiment['predictions'],\n", - " bigram_nb_experiment['predictions'])" + " unigram_nb_experiment_xval['assess_datasets'][0]['y'],\n", + " unigram_nb_experiment_xval['predictions'][0],\n", + " bigram_nb_experiment_xval['predictions'][0])" ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 51, "metadata": {}, "outputs": [ { @@ -1864,7 +1781,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -1872,5 +1789,5 @@ } }, "nbformat": 4, - "nbformat_minor": 1 + "nbformat_minor": 4 } diff --git a/sst_03_neural_networks.ipynb b/sst_03_neural_networks.ipynb index 7940f8a..d1294af 100644 --- a/sst_03_neural_networks.ipynb +++ b/sst_03_neural_networks.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -27,7 +27,7 @@ "1. [Set-up](#Set-up)\n", "1. [Distributed representations as features](#Distributed-representations-as-features)\n", " 1. [GloVe inputs](#GloVe-inputs)\n", - " 1. [IMDB representations](#IMDB-representations)\n", + " 1. [Yelp representations](#Yelp-representations)\n", " 1. [Remarks on this approach](#Remarks-on-this-approach)\n", "1. [RNN classifiers](#RNN-classifiers)\n", " 1. [RNN dataset preparation](#RNN-dataset-preparation)\n", @@ -37,11 +37,7 @@ " 1. [RNN hyperparameter tuning experiment](#RNN-hyperparameter-tuning-experiment)\n", "1. [The VecAvg baseline from Socher et al. 2013](#The-VecAvg-baseline-from-Socher-et-al.-2013)\n", " 1. [Defining the model](#Defining-the-model)\n", - " 1. [VecAvg hyperparameter tuning experiment](#VecAvg-hyperparameter-tuning-experiment)\n", - "1. [Tree-structured neural networks](#Tree-structured-neural-networks)\n", - " 1. [TreeNN dataset preparation](#TreeNN-dataset-preparation)\n", - " 1. [PyTorch TreeNN](#PyTorch-TreeNN)\n", - " 1. [Subtree supervision](#Subtree-supervision)" + " 1. [VecAvg hyperparameter tuning experiment](#VecAvg-hyperparameter-tuning-experiment)" ] }, { @@ -50,15 +46,14 @@ "source": [ "## Overview\n", "\n", - "This notebook defines and explores __vector averaging__, __recurrent neural network (RNN) classifiers__ and __tree-structured neural network (TreeNN) classifiers__ for the Stanford Sentiment Treebank. \n", + "This notebook defines and explores __vector averaging__ and __recurrent neural network (RNN) classifiers__ for the Stanford Sentiment Treebank. \n", "\n", "These approaches make their predictions based on comprehensive representations of the examples: \n", "\n", "* For the vector averaging models, each word is modeled, but we assume that words combine via a simple function that is insensitive to their order or constituent structure.\n", "* For the RNN, each word is again modeled, and we also model the sequential relationships between words.\n", - "* For the TreeNN, the entire parsed structure of the sentence is modeled.\n", "\n", - "All these models contrast with the ones explored in [the previous notebook](sst_02_hand_built_features.ipynb), which make predictions based on more partial, potentially idiosyncratic information extracted from the examples." + "These models contrast with the ones explored in [the previous notebook](sst_02_hand_built_features.ipynb), which make predictions based on more partial, potentially idiosyncratic information extracted from the examples." ] }, { @@ -80,14 +75,12 @@ "import numpy as np\n", "import os\n", "import pandas as pd\n", - "from np_rnn_classifier import RNNClassifier\n", - "from np_tree_nn import TreeNN\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import classification_report\n", "import torch\n", "import torch.nn as nn\n", + "\n", "from torch_rnn_classifier import TorchRNNClassifier\n", - "from torch_tree_nn import TorchTreeNN\n", "import sst\n", "import vsm\n", "import utils" @@ -114,7 +107,7 @@ "\n", "VSMDATA_HOME = os.path.join(DATE_HOME, 'vsmdata')\n", "\n", - "SST_HOME = os.path.join(DATE_HOME, 'trees')" + "SST_HOME = os.path.join(DATE_HOME, 'sentiment')" ] }, { @@ -170,12 +163,12 @@ "metadata": {}, "outputs": [], "source": [ - "def vsm_leaves_phi(tree, lookup, np_func=np.mean):\n", + "def vsm_phi(text, lookup, np_func=np.mean):\n", " \"\"\"Represent `tree` as a combination of the vector of its words.\n", "\n", " Parameters\n", " ----------\n", - " tree : nltk.Tree\n", + " text : str\n", "\n", " lookup : dict\n", " From words to vectors.\n", @@ -192,7 +185,7 @@ " np.array, dimension `X.shape[1]`\n", "\n", " \"\"\"\n", - " allvecs = np.array([lookup[w] for w in tree.leaves() if w in lookup])\n", + " allvecs = np.array([lookup[w] for w in text.split() if w in lookup])\n", " if len(allvecs) == 0:\n", " dim = len(next(iter(lookup.values())))\n", " feats = np.zeros(dim)\n", @@ -207,8 +200,8 @@ "metadata": {}, "outputs": [], "source": [ - "def glove_leaves_phi(tree, np_func=np.sum):\n", - " return vsm_leaves_phi(tree, glove_lookup, np_func=np_func)" + "def glove_phi(text, np_func=np.mean):\n", + " return vsm_phi(text, glove_lookup, np_func=np_func)" ] }, { @@ -222,24 +215,26 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.746 0.789 0.767 941\n", - " positive 0.816 0.778 0.797 1135\n", + " negative 0.613 0.724 0.664 428\n", + " neutral 0.400 0.044 0.079 229\n", + " positive 0.619 0.795 0.696 444\n", "\n", - " accuracy 0.783 2076\n", - " macro avg 0.781 0.783 0.782 2076\n", - "weighted avg 0.785 0.783 0.783 2076\n", + " accuracy 0.611 1101\n", + " macro avg 0.544 0.521 0.480 1101\n", + "weighted avg 0.571 0.611 0.555 1101\n", "\n", - "CPU times: user 2.21 s, sys: 276 ms, total: 2.49 s\n", - "Wall time: 2.01 s\n" + "CPU times: user 2.12 s, sys: 52.9 ms, total: 2.18 s\n", + "Wall time: 2.18 s\n" ] } ], "source": [ "%%time\n", "_ = sst.experiment(\n", - " SST_HOME,\n", - " glove_leaves_phi,\n", + " sst.train_reader(SST_HOME),\n", + " glove_phi,\n", " fit_maxent_classifier,\n", + " assess_dataframes=sst.dev_reader(SST_HOME),\n", " vectorize=False) # Tell `experiment` that we already have our feature vectors." ] }, @@ -247,9 +242,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### IMDB representations\n", + "### Yelp representations\n", "\n", - "Our IMDB VSMs seems pretty well-attuned to the Stanford Sentiment Treebank, so we might think that they can do even better than the general-purpose GloVe inputs. Here are two quick assessments of that idea that seeks to build on ideas we developed in the unit on VSMs." + "Our Yelp VSMs seems pretty well-attuned to the SST, so we might think that they can do even better than the general-purpose GloVe inputs. Here are two quick assessments of that idea that seeks to build on ideas we developed in the unit on VSMs." ] }, { @@ -258,8 +253,8 @@ "metadata": {}, "outputs": [], "source": [ - "imdb20 = pd.read_csv(\n", - " os.path.join(VSMDATA_HOME, 'imdb_window20-flat.csv.gz'), index_col=0)" + "yelp20 = pd.read_csv(\n", + " os.path.join(VSMDATA_HOME, 'yelp_window20-flat.csv.gz'), index_col=0)" ] }, { @@ -268,7 +263,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb20_ppmi = vsm.pmi(imdb20, positive=False)" + "yelp20_ppmi = vsm.pmi(yelp20, positive=False)" ] }, { @@ -277,7 +272,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb20_ppmi_svd = vsm.lsa(imdb20_ppmi, k=300)" + "yelp20_ppmi_svd = vsm.lsa(yelp20_ppmi, k=300)" ] }, { @@ -286,7 +281,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb_lookup = dict(zip(imdb20_ppmi_svd.index, imdb20_ppmi_svd.values))" + "yelp_lookup = dict(zip(yelp20_ppmi_svd.index, yelp20_ppmi_svd.values))" ] }, { @@ -295,8 +290,8 @@ "metadata": {}, "outputs": [], "source": [ - "def imdb_phi(tree, np_func=np.sum):\n", - " return vsm_leaves_phi(tree, imdb_lookup, np_func=np_func)" + "def yelp_phi(text, np_func=np.mean):\n", + " return vsm_leaves_phi(text, yelp_lookup, np_func=np_func)" ] }, { @@ -310,24 +305,26 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.746 0.733 0.739 977\n", - " positive 0.766 0.778 0.772 1099\n", + " negative 0.591 0.673 0.630 428\n", + " neutral 0.423 0.048 0.086 229\n", + " positive 0.560 0.741 0.638 444\n", "\n", - " accuracy 0.757 2076\n", - " macro avg 0.756 0.755 0.756 2076\n", - "weighted avg 0.757 0.757 0.757 2076\n", + " accuracy 0.570 1101\n", + " macro avg 0.525 0.487 0.451 1101\n", + "weighted avg 0.544 0.570 0.520 1101\n", "\n", - "CPU times: user 2.88 s, sys: 1.06 s, total: 3.94 s\n", - "Wall time: 2.04 s\n" + "CPU times: user 3.64 s, sys: 41 ms, total: 3.68 s\n", + "Wall time: 3.69 s\n" ] } ], "source": [ "%%time\n", "_ = sst.experiment(\n", - " SST_HOME,\n", - " imdb_phi,\n", + " sst.train_reader(SST_HOME),\n", + " yelp_phi,\n", " fit_maxent_classifier,\n", + " assess_dataframes=sst.dev_reader(SST_HOME),\n", " vectorize=False) # Tell `experiment` that we already have our feature vectors." ] }, @@ -337,13 +334,13 @@ "source": [ "### Remarks on this approach\n", "\n", - "* Recall that our `unigrams_phi` created feature representations with over 16K dimensions and got about 0.77 with no hyperparameter tuning.\n", + "* Recall that our `unigrams_phi` created feature representations with over 16K dimensions and got about 0.52 with no hyperparameter tuning.\n", "\n", - "* The above models' feature representations have only 300 dimensions, and they are about the same. In many ways, it's striking that we can get a model that is competitive with so few dimensions.\n", + "* The above models' feature representations have only 300 dimensions. While they are struggling with the neutral category, we can probably overcome this with some additional attention to the representations and to our strategies for optimization.\n", "\n", "* The promise of the Mittens model of [Dingwall and Potts 2018](https://arxiv.org/abs/1803.09901) is that we can use GloVe itself to update the general purpose information in the 'glove.6B' vectors with specialized information from one of these IMDB count matrices. That might be worth trying; the `mittens` package (`pip install mittens`) already implements this!\n", "\n", - "* That said, just summing up all the word representations is pretty unappealing linguistically. There's no doubt that we're losing a lot of valuable information in doing this. The models we turn to now can be seen as addressing this shortcoming while retaining the insight that our distributed representations are valuable for this task.\n", + "* That said, just averaging all the word representations is pretty unappealing linguistically. There's no doubt that we're losing a lot of valuable information in doing this. The models we turn to now can be seen as addressing this shortcoming while retaining the insight that our distributed representations are valuable for this task.\n", "\n", "* We'll return to these ideas below, when we consider [the VecAvg baseline from Socher et al. 2013](#The-VecAvg-baseline-from-Socher-et-al.-2013). That model also posits a simple, fixed combination function (averaging). However, it begins with randomly initialized representations and updates them as part of training." ] @@ -397,8 +394,7 @@ "metadata": {}, "outputs": [], "source": [ - "X_rnn_train, y_rnn_train = sst.build_rnn_dataset(\n", - " SST_HOME, sst.train_reader, class_func=sst.binary_class_func)" + "X_rnn_train, y_rnn_train = sst.build_rnn_dataset(sst.train_reader(SST_HOME))" ] }, { @@ -468,8 +464,7 @@ "metadata": {}, "outputs": [], "source": [ - "X_rnn_dev, y_rnn_dev = sst.build_rnn_dataset(\n", - " SST_HOME, sst.dev_reader, class_func=sst.binary_class_func)" + "X_rnn_dev, y_rnn_dev = sst.build_rnn_dataset(sst.dev_reader(SST_HOME))" ] }, { @@ -509,7 +504,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "sst_full_train_vocab has 16,283 items\n" + "sst_full_train_vocab has 18,279 items\n" ] } ], @@ -542,7 +537,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "sst_train_vocab has 7,564 items\n" + "sst_train_vocab has 8,736 items\n" ] } ], @@ -579,15 +574,15 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 52. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.14730898616835475" + "Stopping after epoch 58. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.2520811893045902" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 36.1 s, sys: 435 ms, total: 36.6 s\n", - "Wall time: 8 s\n" + "CPU times: user 6min 37s, sys: 27.9 s, total: 7min 5s\n", + "Wall time: 2min 52s\n" ] } ], @@ -615,12 +610,13 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.702 0.743 0.722 428\n", - " positive 0.737 0.696 0.716 444\n", + " negative 0.589 0.565 0.577 428\n", + " neutral 0.250 0.249 0.249 229\n", + " positive 0.621 0.646 0.634 444\n", "\n", - " accuracy 0.719 872\n", - " macro avg 0.720 0.719 0.719 872\n", - "weighted avg 0.720 0.719 0.719 872\n", + " accuracy 0.532 1101\n", + " macro avg 0.487 0.487 0.487 1101\n", + "weighted avg 0.531 0.532 0.532 1101\n", "\n" ] } @@ -688,15 +684,15 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 23. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.12253877334296703" + "Stopping after epoch 22. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.7556907385587692" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 15 s, sys: 14.7 ms, total: 15 s\n", - "Wall time: 2.74 s\n" + "CPU times: user 3min 7s, sys: 16.6 s, total: 3min 23s\n", + "Wall time: 1min 29s\n" ] } ], @@ -724,12 +720,13 @@ "text": [ " precision recall f1-score support\n", "\n", - " negative 0.824 0.724 0.771 428\n", - " positive 0.762 0.851 0.804 444\n", + " negative 0.642 0.757 0.695 428\n", + " neutral 0.250 0.157 0.193 229\n", + " positive 0.695 0.707 0.701 444\n", "\n", - " accuracy 0.789 872\n", - " macro avg 0.793 0.788 0.788 872\n", - "weighted avg 0.793 0.789 0.788 872\n", + " accuracy 0.612 1101\n", + " macro avg 0.529 0.540 0.529 1101\n", + "weighted avg 0.582 0.612 0.593 1101\n", "\n" ] } @@ -760,8 +757,8 @@ "metadata": {}, "outputs": [], "source": [ - "def simple_leaves_phi(tree):\n", - " return tree.leaves()" + "def simple_leaves_phi(text):\n", + " return text.split()" ] }, { @@ -781,9 +778,9 @@ " # There are lots of other parameters and values we could\n", " # explore, but this is at least a solid start:\n", " param_grid = {\n", - " 'embed_dim': [25, 50, 75, 100],\n", - " 'hidden_dim': [25, 50, 75, 100],\n", - " 'eta': [0.001, 0.01, 0.05]}\n", + " 'embed_dim': [50, 75, 100],\n", + " 'hidden_dim': [50, 75, 100],\n", + " 'eta': [0.001, 0.01]}\n", "\n", " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", " X, y, basemod, cv=3, param_grid=param_grid)\n", @@ -800,35 +797,37 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 13. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 3.154094541274389555" + "Stopping after epoch 16. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.7026695416478938" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Best params: {'embed_dim': 75, 'eta': 0.001, 'hidden_dim': 75}\n", - "Best score: 0.791\n", + "Best params: {'embed_dim': 100, 'eta': 0.001, 'hidden_dim': 100}\n", + "Best score: 0.547\n", " precision recall f1-score support\n", "\n", - " negative 0.769 0.834 0.800 1002\n", - " positive 0.832 0.766 0.798 1074\n", + " negative 0.668 0.668 0.668 428\n", + " neutral 0.291 0.218 0.249 229\n", + " positive 0.667 0.752 0.707 444\n", "\n", - " accuracy 0.799 2076\n", - " macro avg 0.801 0.800 0.799 2076\n", - "weighted avg 0.802 0.799 0.799 2076\n", + " accuracy 0.609 1101\n", + " macro avg 0.542 0.546 0.541 1101\n", + "weighted avg 0.589 0.609 0.597 1101\n", "\n", - "CPU times: user 34min 15s, sys: 15.6 s, total: 34min 30s\n", - "Wall time: 34min 16s\n" + "CPU times: user 6h 7min 58s, sys: 22min 13s, total: 6h 30min 12s\n", + "Wall time: 3h 35min 2s\n" ] } ], "source": [ "%%time\n", "rnn_experiment_xval = sst.experiment(\n", - " SST_HOME,\n", + " sst.train_reader(SST_HOME),\n", " simple_leaves_phi,\n", " fit_rnn_with_hyperparameter_search,\n", + " assess_dataframes=sst.dev_reader(SST_HOME),\n", " vectorize=False)" ] }, @@ -836,68 +835,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Here we carry forward the optimal model from our hyperparameter search, to run a final assessment on the test set:" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "def fit_optimized_rnn(X, y):\n", - " mod = rnn_experiment_xval['model']\n", - " mod.fit(X, y)\n", - " return mod" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 12. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 2.3395959859716413" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " precision recall f1-score support\n", - "\n", - " negative 0.815 0.826 0.820 912\n", - " positive 0.823 0.812 0.817 909\n", - "\n", - " accuracy 0.819 1821\n", - " macro avg 0.819 0.819 0.819 1821\n", - "weighted avg 0.819 0.819 0.819 1821\n", - "\n", - "CPU times: user 21.4 s, sys: 102 ms, total: 21.5 s\n", - "Wall time: 21.4 s\n" - ] - } - ], - "source": [ - "%%time\n", - "_ = sst.experiment(\n", - " SST_HOME,\n", - " simple_leaves_phi,\n", - " fit_optimized_rnn,\n", - " class_func=sst.binary_class_func,\n", - " train_reader=(sst.train_reader, sst.dev_reader),\n", - " assess_reader=sst.test_reader,\n", - " vectorize=False)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This model looks quite competitive with the simpler models we explored previously, and perhaps an even wider hyperparameter search would lead to additional improvements. In [contextualreps.ipynb](contextualreps.ipynb), we look at variants of the above that involve fine-tuning with ELMo and BERT, and those models achieve results around 0.90 on the test set, which further highlights the value of rich pretraining." + "This model looks quite competitive with the simpler models we explored previously, and perhaps an even wider hyperparameter search would lead to additional improvements. In [finetuning.ipynb](finetuning.ipynb), we look at variants of the above that involve fine-tuning with BERT, and those models achieve even better results, which further highlights the value of rich pretraining." ] }, { @@ -922,7 +860,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -958,7 +896,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -978,131 +916,102 @@ "source": [ "### VecAvg hyperparameter tuning experiment\n", "\n", - "Now that we have the model implemented, let's see if we can reproduce Socher et al.'s 80.1 on the binary, root-only version of SST.\n", - "\n", - "First, we do the hyperparameter search:" + "Now that we have the model implemented, let's see if we can reproduce Socher et al.'s 80.1 on the binary, root-only version of SST." ] }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ - "def fit_vecavg_with_hyperparameter_search(X, y):\n", - " basemod = TorchVecAvgClassifier(\n", - " sst_train_vocab,\n", - " early_stopping=True)\n", + "train_df = sst.train_reader(SST_HOME)\n", "\n", - " param_grid = {\n", - " 'embed_dim': [50, 100, 200, 300],\n", - " 'eta': [0.001, 0.01, 0.05]}\n", - "\n", - " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", - " X, y, basemod, cv=3, param_grid=param_grid)\n", - "\n", - " return bestmod" + "train_bin_df = train_df[train_df.label != 'neutral']" ] }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 39, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 18. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.080092592164874088" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Best params: {'embed_dim': 300, 'eta': 0.01}\n", - "Best score: 0.766\n", - " precision recall f1-score support\n", - "\n", - " negative 0.786 0.715 0.749 1011\n", - " positive 0.751 0.815 0.782 1065\n", - "\n", - " accuracy 0.766 2076\n", - " macro avg 0.768 0.765 0.765 2076\n", - "weighted avg 0.768 0.766 0.766 2076\n", - "\n", - "CPU times: user 16min 49s, sys: 23.2 s, total: 17min 13s\n", - "Wall time: 4min 47s\n" - ] - } - ], + "outputs": [], "source": [ - "%%time\n", - "vecavg_experiment_xval = sst.experiment(\n", - " SST_HOME,\n", - " simple_leaves_phi,\n", - " fit_vecavg_with_hyperparameter_search,\n", - " vectorize=False)" + "dev_df = sst.dev_reader(SST_HOME)\n", + "\n", + "dev_bin_df = dev_df[dev_df.label != 'neutral']" ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 40, "metadata": {}, + "outputs": [], "source": [ - "And then we use the best parameters found above to train a new model on the union of the train and dev sets:" + "test_df = sst.sentiment_reader(os.path.join(SST_HOME, \"sst3-test-labeled.csv\"))\n", + "\n", + "test_bin_df = test_df[test_df.label != 'neutral']" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ - "def fit_optimized_vecavg(X, y):\n", - " mod = vecavg_experiment_xval['model']\n", - " mod.fit(X, y)\n", - " return mod" + "def fit_vecavg_with_hyperparameter_search(X, y):\n", + " basemod = TorchVecAvgClassifier(\n", + " sst_train_vocab,\n", + " early_stopping=True)\n", + "\n", + " param_grid = {\n", + " 'embed_dim': [50, 100, 200, 300],\n", + " 'eta': [0.001, 0.01, 0.05]}\n", + "\n", + " bestmod = utils.fit_classifier_with_hyperparameter_search(\n", + " X, y, basemod, cv=3, param_grid=param_grid)\n", + "\n", + " return bestmod" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 42, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 17. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.14763524942100048" + "Stopping after epoch 13. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 0.037477616686373956" ] }, { "name": "stdout", "output_type": "stream", "text": [ + "Best params: {'embed_dim': 100, 'eta': 0.05}\n", + "Best score: 0.784\n", " precision recall f1-score support\n", "\n", - " negative 0.798 0.823 0.811 912\n", - " positive 0.817 0.791 0.804 909\n", + " negative 0.779 0.814 0.796 912\n", + " positive 0.804 0.768 0.786 909\n", "\n", - " accuracy 0.807 1821\n", - " macro avg 0.808 0.807 0.807 1821\n", - "weighted avg 0.808 0.807 0.807 1821\n", + " accuracy 0.791 1821\n", + " macro avg 0.791 0.791 0.791 1821\n", + "weighted avg 0.791 0.791 0.791 1821\n", "\n", - "CPU times: user 29.5 s, sys: 2.14 s, total: 31.6 s\n", - "Wall time: 9.93 s\n" + "CPU times: user 21min 22s, sys: 1min 9s, total: 22min 31s\n", + "Wall time: 12min 1s\n" ] } ], "source": [ "%%time\n", - "_= sst.experiment(\n", - " SST_HOME,\n", + "vecavg_experiment_xval = sst.experiment(\n", + " [train_bin_df, dev_bin_df],\n", " simple_leaves_phi,\n", - " fit_optimized_vecavg,\n", - " class_func=sst.binary_class_func,\n", - " train_reader=(sst.train_reader, sst.dev_reader),\n", - " assess_reader=sst.test_reader,\n", + " fit_vecavg_with_hyperparameter_search,\n", + " assess_dataframes=test_bin_df,\n", " vectorize=False)" ] }, @@ -1112,169 +1021,6 @@ "source": [ "Excellent – it looks like we basically reproduced the number from the paper (80.1)." ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Tree-structured neural networks\n", - "\n", - "Tree-structured neural networks (TreeNNs) are close relatives of RNN classifiers. (If you tilt your head, you can see the above sequence model as a kind of tree.) The TreeNNs we explore here are the simplest possible and actually have many fewer parameters than RNNs. Here's a summary:\n", - "\n", - "\n", - "\n", - "The crucial property of these networks is the way they employ recursion: the representation of a parent node $p$ has the same dimensionality as the word representations, allowing seamless repeated application of the central combination function:\n", - "\n", - "$$p = \\tanh([x_{L};x_{R}]W_{wh} + b)$$\n", - "\n", - "Here, $[x_{L};x_{R}]$ is the concatenation of the left and right child representations, and $p$ is the resulting parent node, which can then be a child node in a higher subtree.\n", - "\n", - "When we reach the root node $h_{r}$ of the tree, we apply a softmax classifier using that top node's representation:\n", - "\n", - "$$y = \\textbf{softmax}(h_{r}W_{hy} + b)$$" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### TreeNN dataset preparation\n", - "\n", - "This is the only model under consideration here that makes use of the tree structures in the SST:" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [], - "source": [ - "X_tree_train, y_tree_train = sst.build_tree_dataset(\n", - " SST_HOME, sst.train_reader, class_func=sst.binary_class_func)" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "Tree('positive', [Tree(None, [Tree(None, ['The']), Tree(None, ['Rock'])]), Tree('positive', [Tree('positive', [Tree(None, ['is']), Tree('positive', [Tree(None, ['destined']), Tree(None, [Tree(None, [Tree(None, [Tree(None, [Tree(None, ['to']), Tree(None, [Tree(None, ['be']), Tree(None, [Tree(None, ['the']), Tree(None, [Tree(None, ['21st']), Tree(None, [Tree(None, [Tree(None, ['Century']), Tree(None, [\"'s\"])]), Tree(None, [Tree('positive', ['new']), Tree(None, [Tree(None, ['``']), Tree(None, ['Conan'])])])])])])])]), Tree(None, [\"''\"])]), Tree(None, ['and'])]), Tree('positive', [Tree(None, ['that']), Tree('positive', [Tree(None, ['he']), Tree('positive', [Tree(None, [\"'s\"]), Tree('positive', [Tree(None, ['going']), Tree('positive', [Tree(None, ['to']), Tree('positive', [Tree('positive', [Tree(None, ['make']), Tree('positive', [Tree('positive', [Tree(None, ['a']), Tree('positive', ['splash'])]), Tree(None, [Tree(None, ['even']), Tree('positive', ['greater'])])])]), Tree(None, [Tree(None, ['than']), Tree(None, [Tree(None, [Tree(None, [Tree(None, [Tree('negative', [Tree(None, ['Arnold']), Tree(None, ['Schwarzenegger'])]), Tree(None, [','])]), Tree(None, [Tree(None, ['Jean-Claud']), Tree(None, [Tree(None, ['Van']), Tree(None, ['Damme'])])])]), Tree(None, ['or'])]), Tree(None, [Tree(None, ['Steven']), Tree(None, ['Segal'])])])])])])])])])])])])]), Tree(None, ['.'])])])" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "X_tree_train[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "metadata": {}, - "outputs": [], - "source": [ - "X_tree_dev, y_tree_dev = sst.build_tree_dataset(\n", - " SST_HOME, sst.dev_reader, class_func=sst.binary_class_func)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### PyTorch TreeNN" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [], - "source": [ - "torch_tree_nn_glove = TorchTreeNN(\n", - " sst_glove_vocab,\n", - " embedding=glove_embedding,\n", - " max_grad_norm=10.0,\n", - " early_stopping=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Stopping after epoch 33. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 4.148158252239227" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 26min 57s, sys: 175 ms, total: 26min 57s\n", - "Wall time: 26min 41s\n" - ] - } - ], - "source": [ - "%time _ = torch_tree_nn_glove.fit(X_tree_train, y_tree_train)" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "metadata": {}, - "outputs": [], - "source": [ - "tree_dev_preds = torch_tree_nn_glove.predict(X_tree_dev)" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " precision recall f1-score support\n", - "\n", - " negative 0.574 0.605 0.589 428\n", - " positive 0.599 0.568 0.583 444\n", - "\n", - " accuracy 0.586 872\n", - " macro avg 0.586 0.586 0.586 872\n", - "weighted avg 0.587 0.586 0.586 872\n", - "\n" - ] - } - ], - "source": [ - "print(classification_report(y_tree_dev, tree_dev_preds, digits=3))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Subtree supervision\n", - "\n", - "We've so far ignored one of the most exciting aspects of the SST: it has sentiment labels on every constituent from the root down to the lexical nodes. \n", - "\n", - "It is fairly easy to extend `TorchTreeNN` to learn from these additional labels. The key change is that the recursive interpretation function has to gather all of the node representations and their true labels and pass these to the loss function:\n", - "\n", - "" - ] } ], "metadata": { @@ -1293,7 +1039,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -1301,5 +1047,5 @@ } }, "nbformat": 4, - "nbformat_minor": 1 + "nbformat_minor": 4 } diff --git a/test/notebook_tester.py b/test/notebook_tester.py index f8c3dc7..be40f11 100644 --- a/test/notebook_tester.py +++ b/test/notebook_tester.py @@ -4,7 +4,7 @@ import subprocess __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" TEMP_PREFIX = "TEMP_" diff --git a/test/test_autoencoders.py b/test/test_autoencoders.py index 1f65495..56fb2b4 100644 --- a/test/test_autoencoders.py +++ b/test/test_autoencoders.py @@ -13,7 +13,7 @@ from np_autoencoder import simple_example as np_simple_example __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_colors.py b/test/test_colors.py index 823ea0e..1491323 100644 --- a/test/test_colors.py +++ b/test/test_colors.py @@ -5,7 +5,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_glove.py b/test/test_glove.py index 7de0c5f..0177ac4 100644 --- a/test/test_glove.py +++ b/test/test_glove.py @@ -10,7 +10,7 @@ from np_glove import GloVe __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_nli.py b/test/test_nli.py index 836f079..22274d3 100644 --- a/test/test_nli.py +++ b/test/test_nli.py @@ -10,7 +10,7 @@ __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_np_model_gradients.py b/test/test_np_model_gradients.py index e3b7b24..55b8a32 100644 --- a/test/test_np_model_gradients.py +++ b/test/test_np_model_gradients.py @@ -8,7 +8,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_rel_ext.py b/test/test_rel_ext.py index f40499e..d24cc8c 100644 --- a/test/test_rel_ext.py +++ b/test/test_rel_ext.py @@ -5,7 +5,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_retrofitting.py b/test/test_retrofitting.py index af43f25..822378f 100644 --- a/test/test_retrofitting.py +++ b/test/test_retrofitting.py @@ -6,7 +6,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_rnn_classifiers.py b/test/test_rnn_classifiers.py index 0262cda..b0679db 100644 --- a/test/test_rnn_classifiers.py +++ b/test/test_rnn_classifiers.py @@ -16,7 +16,7 @@ from torch_rnn_classifier import TorchRNNClassifier, simple_example __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_sgd_classifier.py b/test/test_sgd_classifier.py index 47dc3b1..245f732 100644 --- a/test/test_sgd_classifier.py +++ b/test/test_sgd_classifier.py @@ -9,7 +9,7 @@ from np_sgd_classifier import simple_example __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_shallow_neural_classifiers.py b/test/test_shallow_neural_classifiers.py index a008fba..6c25214 100644 --- a/test/test_shallow_neural_classifiers.py +++ b/test/test_shallow_neural_classifiers.py @@ -16,7 +16,7 @@ from torch_shallow_neural_classifier import simple_example __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_sst.py b/test/test_sst.py index c86b24c..661e4aa 100644 --- a/test/test_sst.py +++ b/test/test_sst.py @@ -7,87 +7,75 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() -sst_home = os.path.join('data', 'trees') +sst_home = os.path.join('data', 'sentiment') -@pytest.mark.parametrize("reader, count", [ - [sst.train_reader(sst_home, class_func=None), 8544], - [sst.train_reader(sst_home, class_func=sst.binary_class_func), 6920], - [sst.train_reader(sst_home, class_func=sst.ternary_class_func), 8544], - [sst.dev_reader(sst_home, class_func=None), 1101], - [sst.dev_reader(sst_home, class_func=sst.binary_class_func), 872], - [sst.dev_reader(sst_home, class_func=sst.ternary_class_func), 1101], - +@pytest.mark.parametrize("split_df, expected_count", [ + [sst.train_reader(sst_home, include_subtrees=True, dedup=False), 318582], + [sst.train_reader(sst_home, include_subtrees=True, dedup=True), 159274], + [sst.train_reader(sst_home, include_subtrees=False, dedup=False), 8544], + [sst.train_reader(sst_home, include_subtrees=False, dedup=True), 8534], + [sst.dev_reader(sst_home, include_subtrees=True, dedup=False), 1101], + [sst.dev_reader(sst_home, include_subtrees=True, dedup=True), 1100], + [sst.dev_reader(sst_home, include_subtrees=False, dedup=False), 1101], + [sst.dev_reader(sst_home, include_subtrees=False, dedup=True), 1100] ]) -def test_readers(reader, count): - result = len(list(reader)) - assert result == count - - -def test_reader_labeling(): - tree, label = next(sst.train_reader(sst_home, class_func=sst.ternary_class_func)) - for subtree in tree.subtrees(): - assert subtree.label() in {'negative', 'neutral', 'positive'} +def test_readers(split_df, expected_count): + result = split_df.shape[0] + assert result == expected_count def test_build_dataset_vectorizing(): - phi = lambda tree: Counter(tree.leaves()) - class_func = None - reader = sst.train_reader + phi = lambda text: Counter(text.split()) + split_df = sst.dev_reader(sst_home) dataset = sst.build_dataset( - sst_home, - reader, + split_df, phi, - class_func, vectorizer=None, vectorize=True) - assert len(dataset['X']) == len(list(reader(sst_home))) + assert len(dataset['X']) == split_df.shape[0] assert len(dataset['y']) == len(dataset['X']) assert len(dataset['raw_examples']) == len(dataset['X']) def test_build_dataset_not_vectorizing(): - phi = lambda tree: tree - class_func = None - reader = sst.train_reader + phi = lambda text: text + split_df = sst.dev_reader(sst_home) dataset = sst.build_dataset( - sst_home, - reader, + split_df, phi, - class_func, vectorizer=None, vectorize=False) - assert len(dataset['X']) == len(list(reader(sst_home))) + assert len(dataset['X']) == split_df.shape[0] assert dataset['X'] == dataset['raw_examples'] assert len(dataset['y']) == len(dataset['X']) def test_build_rnn_dataset(): - X, y = sst.build_rnn_dataset( - sst_home, sst.train_reader, class_func=sst.binary_class_func) - assert len(X) == 6920 - assert len(y) == 6920 + split_df = sst.dev_reader(sst_home) + X, y = sst.build_rnn_dataset(split_df) + assert len(X) == 1101 + assert len(y) == 1101 -@pytest.mark.parametrize("assess_reader", [ +@pytest.mark.parametrize("assess_dataframe", [ None, - sst.dev_reader + sst.dev_reader(sst_home) ]) -def test_experiment(assess_reader): +def test_experiment(assess_dataframe): def fit_maxent(X, y): mod = LogisticRegression(solver='liblinear', multi_class='auto') mod.fit(X, y) return mod sst.experiment( - sst_home, - train_reader=sst.train_reader, + sst.train_reader(sst_home, include_subtrees=False), phi=lambda x: {"$UNK": 1}, train_func=fit_maxent, - assess_reader=assess_reader, + assess_dataframes=assess_dataframe, random_state=42) diff --git a/test/test_torch_color_describer.py b/test/test_torch_color_describer.py index d762cbb..09046c9 100644 --- a/test/test_torch_color_describer.py +++ b/test/test_torch_color_describer.py @@ -11,7 +11,7 @@ from torch_color_describer import simple_example __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_torch_model_base.py b/test/test_torch_model_base.py index 3a1d2d8..7c2fc71 100644 --- a/test/test_torch_model_base.py +++ b/test/test_torch_model_base.py @@ -12,7 +12,7 @@ from torch_model_base import TorchModelBase __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_tree_nns.py b/test/test_tree_nns.py index 28f8737..3368e5a 100644 --- a/test/test_tree_nns.py +++ b/test/test_tree_nns.py @@ -15,7 +15,7 @@ from np_tree_nn import simple_example as np_simple_example __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_utils.py b/test/test_utils.py index 2b7c3cc..1c9d5d7 100644 --- a/test/test_utils.py +++ b/test/test_utils.py @@ -5,7 +5,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() diff --git a/test/test_vsm.py b/test/test_vsm.py index d1810ee..9706e68 100644 --- a/test/test_vsm.py +++ b/test/test_vsm.py @@ -1,16 +1,24 @@ import numpy as np +import os import pandas as pd import pytest +import torch +from transformers import BertModel, BertTokenizer + import vsm import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" utils.fix_random_seeds() +DATA_HOME = os.path.join('data', 'vsmdata') +REL_HOME = os.path.join('data', 'wordrelatedness') + + @pytest.fixture def df(): vocab = ['ab', 'bc', 'cd', 'de'] @@ -23,6 +31,20 @@ def df(): return df +@pytest.fixture +def count_dfs(): + dfs = {} + basenames = ( + 'yelp_window5-scaled.csv.gz', + 'yelp_window20-flat.csv.gz', + 'giga_window5-scaled.csv.gz', + 'giga_window20-flat.csv.gz') + for basename in basenames: + dfs[basename] = pd.read_csv( + os.path.join(DATA_HOME, basename), index_col=0) + return dfs + + @pytest.mark.parametrize("arg, expected", [ [ np.array([[34.0, 11.0], [ 47.0, 7.0]]), @@ -109,3 +131,135 @@ def test_tsne_viz(df): def test_lsa(df): vsm.lsa(df, k=2) + + +@pytest.mark.parametrize("basename1, basename2", [ + ['yelp_window5-scaled.csv.gz', 'yelp_window20-flat.csv.gz'], + ['yelp_window20-flat.csv.gz', 'giga_window5-scaled.csv.gz'], + ['giga_window5-scaled.csv.gz', 'giga_window20-flat.csv.gz'] +]) +def test_count_matrix_index_identity(basename1, basename2, count_dfs): + df1 = count_dfs[basename1] + df2 = count_dfs[basename2] + assert df1.index.equals(df2.index) + + +@pytest.mark.parametrize("batch_ids, expected_shape", [ + ( + [[101, 14324, 102]], (1, 3, 768) + ) +]) +def test_hf_represent(batch_ids, expected_shape): + """Really just tests that the function works.""" + batch_ids = torch.LongTensor(batch_ids) + model = BertModel.from_pretrained('bert-base-uncased') + reps = vsm.hf_represent(batch_ids, model, layer=-1) + assert reps.shape == expected_shape + + +@pytest.mark.parametrize("text, add_special_tokens, expected_len", [ + ("the cat", True, 4), + ("the cat", False, 2) +]) +def test_hf_encode(text, add_special_tokens, expected_len): + """Really just tests that the function works.""" + tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') + encoding = vsm.hf_encode( + text, tokenizer, add_special_tokens=add_special_tokens) + assert encoding.shape == (1, expected_len) + + +@pytest.mark.parametrize("X, expected", [ + ([[[1., 2, 3], [4., 5, 6]]], [[2.5, 3.5, 4.5]]) +]) +def test_mean_pooling(X, expected): + X = torch.tensor(X) + expected = torch.tensor(expected) + result = vsm.mean_pooling(X) + assert torch.equal(result, expected) + + +@pytest.mark.parametrize("X, expected", [ + [ + [[[1., 4, 3], [4., 2, 6]]], + [[4., 4, 6]] + ], + [ + [[[1., 4, 3], [4., 2, 6]], [[1., 4, 3], [4., 2, 6]]], + [[4., 4, 6], [4., 4, 6]] + ], +]) +def test_max_pooling(X, expected): + X = torch.tensor(X) + expected = torch.tensor(expected) + result = vsm.max_pooling(X) + assert torch.equal(result, expected) + + +@pytest.mark.parametrize("X, expected", [ + [ + [[[1., 4, 3], [4., 2, 6]]], + [[1., 2, 3]] + ], + [ + [[[1., 4, 3], [4., 2, 6]], [[4, 3, 2], [2, 3, 4.]]], + [[1., 2, 3], [2., 3, 2]] + ] +]) +def test_min_pooling(X, expected): + X = torch.tensor(X) + expected = torch.tensor(expected) + result = vsm.min_pooling(X) + assert torch.equal(result, expected) + + +@pytest.mark.parametrize("X, expected", [ + [ + [[[1., 4, 3], [4., 2, 6]]], + [[4., 2, 6]] + ], + [ + [[[1., 4, 3], [4., 2, 6]], [[4, 3, 2], [2, 3, 4.]]], + [[4., 2, 6], [2., 3, 4]] + ] +]) +def test_last_pooling(X, expected): + X = torch.tensor(X) + expected = torch.tensor(expected) + result = vsm.last_pooling(X) + assert torch.equal(result, expected) + + +@pytest.mark.parametrize("pool_func", [ + vsm.mean_pooling, + vsm.max_pooling, + vsm.min_pooling, + vsm.last_pooling +]) +def test_pool_func_shape_check_raise(pool_func): + hidden_states = torch.Tensor([1,2]) + with pytest.raises(ValueError): + pool_func(hidden_states) + + +def test_create_subword_pooling_vsm(): + """Really just tests that the function works.""" + vocab = ["puppy", "snuffleupagus"] + bert_weights_name = 'bert-base-uncased' + tokenizer = BertTokenizer.from_pretrained(bert_weights_name) + model = BertModel.from_pretrained(bert_weights_name) + df = vsm.create_subword_pooling_vsm( + vocab, tokenizer, model, + layer=1, pool_func=vsm.mean_pooling) + assert list(df.index) == vocab + + +def test_word_relatedness_evaluation(): + """Really just tests that the function works.""" + dev_df = pd.read_csv( + os.path.join(REL_HOME, "cs224u-wordrelatedness-dev.csv")) + count_df = pd.read_csv( + os.path.join(DATA_HOME, "giga_window5-scaled.csv.gz"), index_col=0) + count_pred_df, count_rho = vsm.word_relatedness_evaluation(dev_df, count_df) + assert isinstance(count_rho, float) + assert 'prediction' in count_pred_df.columns diff --git a/torch_autoencoder.py b/torch_autoencoder.py index 2a580a3..23c9b83 100644 --- a/torch_autoencoder.py +++ b/torch_autoencoder.py @@ -7,7 +7,7 @@ from torch_model_base import TorchModelBase __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class TorchAutoencoder(TorchModelBase): diff --git a/torch_color_describer.py b/torch_color_describer.py index f0fa521..687ed4d 100644 --- a/torch_color_describer.py +++ b/torch_color_describer.py @@ -2,6 +2,7 @@ import itertools import nltk.translate.bleu_score import numpy as np +from sklearn.metrics import accuracy_score import torch import torch.nn as nn import torch.utils.data @@ -10,7 +11,7 @@ from utils import START_SYMBOL, END_SYMBOL, UNK_SYMBOL __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class ColorDataset(torch.utils.data.Dataset): @@ -230,7 +231,7 @@ def forward(self, word_seqs, seq_lengths=None, hidden=None, target_colors=None): embs = torch.nn.utils.rnn.pack_padded_sequence( embs, batch_first=True, - lengths=seq_lengths, + lengths=seq_lengths.cpu(), enforce_sorted=False) # RNN forward: output, hidden = self.rnn(embs, hidden) @@ -708,9 +709,9 @@ def listener_predict_one(self, context, seq, device=None): pred_index = orders[order_index][-1] return min_perp, pred_color, pred_index - def listener_accuracy(self, color_seqs, word_seqs, device=None): + def listener_predictions(self, color_seqs, word_seqs, device=None): """ - Compute the "listener accuracy" of the model for each example. + Compute the listener predictions of the model for each example. For the ith example, this is defined as prediction = max_{c in C_i} P(word_seq[i] | c) @@ -741,16 +742,30 @@ def listener_accuracy(self, color_seqs, word_seqs, device=None): Returns ------- - list of float + tuple of lists, the first member giving the gold target indices + and the second giving the predicted target indices. """ + gold = [] + predicted = [] correct = 0 for color_seq, word_seq in zip(color_seqs, word_seqs): target_index = len(color_seq) - 1 min_perp, pred, pred_index = self.listener_predict_one( color_seq, word_seq, device=device) - correct += int(target_index == pred_index) - return correct / len(color_seqs) + gold.append(target_index) + predicted.append(pred_index) + return gold, predicted + + def listener_accuracy(self, color_seqs, word_seqs, device=None): + """ + Returns the listener accuracy as calculated based on values + returns by `listener_predictions`. + + """ + gold, predicted = self.listener_predictions( + color_seqs, word_seqs, device=device) + return accuracy_score(gold, predicted) def score(self, color_seqs, word_seqs, device=None): """ @@ -779,7 +794,8 @@ def corpus_bleu(self, color_seqs, word_seqs): Returns ------- - float + tuple consisting of the bleu score (float) and the predictions + as a list of lists of tokens """ # Ideally, we would have multiple references for each context, @@ -793,7 +809,7 @@ def corpus_bleu(self, color_seqs, word_seqs): bleu = nltk.translate.bleu_score.corpus_bleu( refs, preds, weights=(1, )) - return bleu + return bleu, preds def evaluate(self, color_seqs, word_seqs, device=None): """ @@ -818,12 +834,23 @@ def evaluate(self, color_seqs, word_seqs, device=None): Returns ------- - dict, {"listener_accuracy": float, 'corpus_bleu': float} - - """ - acc = self.listener_accuracy(color_seqs, word_seqs, device=device) - bleu = self.corpus_bleu(color_seqs, word_seqs) - return {"listener_accuracy": acc, 'corpus_bleu': bleu} + dict, { + "listener_accuracy": float, + "corpus_bleu": float, + "target_index": list of int, + "predicted_index": list of int} + + """ + gold, predicted = self.listener_predictions( + color_seqs, word_seqs, device=device) + acc = accuracy_score(gold, predicted) + bleu, pred_utt = self.corpus_bleu(color_seqs, word_seqs) + return { + "listener_accuracy": acc, + "corpus_bleu": bleu, + "target_index": gold, + "predicted_index": predicted, + "predicted_utterance": pred_utt} diff --git a/torch_glove.py b/torch_glove.py index 2cab679..10be5e7 100644 --- a/torch_glove.py +++ b/torch_glove.py @@ -7,7 +7,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class TorchGloVeDataset(torch.utils.data.Dataset): diff --git a/torch_model_base.py b/torch_model_base.py index 91ed7ca..f537750 100644 --- a/torch_model_base.py +++ b/torch_model_base.py @@ -7,7 +7,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class TorchModelBase: diff --git a/torch_rnn_classifier.py b/torch_rnn_classifier.py index 7ec0e4f..d56aa4a 100644 --- a/torch_rnn_classifier.py +++ b/torch_rnn_classifier.py @@ -7,7 +7,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class TorchRNNDataset(torch.utils.data.Dataset): @@ -129,7 +129,10 @@ def forward(self, X, seq_lengths): if self.use_embedding: X = self.embedding(X) embs = torch.nn.utils.rnn.pack_padded_sequence( - X, batch_first=True, lengths=seq_lengths, enforce_sorted=False) + X, + batch_first=True, + lengths=seq_lengths.cpu(), + enforce_sorted=False) outputs, state = self.rnn(embs) return outputs, state diff --git a/torch_shallow_neural_classifier.py b/torch_shallow_neural_classifier.py index 9c7ab7b..a4446d9 100644 --- a/torch_shallow_neural_classifier.py +++ b/torch_shallow_neural_classifier.py @@ -6,7 +6,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class TorchShallowNeuralClassifier(TorchModelBase): diff --git a/torch_tree_nn.py b/torch_tree_nn.py index 6af1fef..ad1d7fb 100644 --- a/torch_tree_nn.py +++ b/torch_tree_nn.py @@ -6,7 +6,7 @@ import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" class TorchTreeNNModel(nn.Module): diff --git a/tutorial_jupyter_notebooks.ipynb b/tutorial_jupyter_notebooks.ipynb index b7ea426..5336cb7 100644 --- a/tutorial_jupyter_notebooks.ipynb +++ b/tutorial_jupyter_notebooks.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Lucy Li\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -125,7 +125,7 @@ "# toggle the output\n", "# toggle scrolling to make long output smaller\n", "# clear the output\n", - "for i in range(50): \n", + "for i in range(50):\n", " print(\"cats\")" ] }, @@ -137,7 +137,7 @@ "source": [ "# run this cell and stop before it finishes\n", "# stop acts like a KeyboardInterrupt\n", - "for i in range(50): \n", + "for i in range(50):\n", " time.sleep(1) # make loop run slowly\n", " print(\"cats\")" ] @@ -149,11 +149,11 @@ "outputs": [], "source": [ "# running this cell leads to no output\n", - "def function1(): \n", + "def function1():\n", " print(\"dogs\")\n", "\n", "# put cursor in front of this comment and split and merge this cell.\n", - "def function2(): \n", + "def function2():\n", " print(\"cheese\")" ] }, @@ -214,8 +214,8 @@ "metadata": {}, "outputs": [], "source": [ - "# depending on the number of times you ran \n", - "# cells B and C, the output of this cell will \n", + "# depending on the number of times you ran\n", + "# cells B and C, the output of this cell will\n", "# be different.\n", "a" ] @@ -432,9 +432,9 @@ "outputs": [], "source": [ "# play around with this cell with shortcuts\n", - "# delete this cell \n", + "# delete this cell\n", "# Edit -> Undo Delete Cells\n", - "for i in range(10): \n", + "for i in range(10):\n", " print(\"jelly beans\")" ] }, @@ -451,9 +451,7 @@ }, { "cell_type": "markdown", - "metadata": { - "collapsed": true - }, + "metadata": {}, "source": [ "## Extras" ] @@ -520,9 +518,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/tutorial_numpy.ipynb b/tutorial_numpy.ipynb index 92c142b..5885748 100644 --- a/tutorial_numpy.ipynb +++ b/tutorial_numpy.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts, Will Monroe, and Lucy Li\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -70,7 +70,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -86,27 +86,60 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0.])" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.zeros(5)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 1., 1., 1., 1.])" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.ones(5)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5])" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# convert list to numpy array\n", "np.array([1,2,3,4,5])" @@ -114,9 +147,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[1.0, 1.0, 1.0, 1.0, 1.0]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# convert numpy array to list\n", "np.ones(5).tolist()" @@ -124,9 +168,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 2., 3., 4., 5.])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# one float => all floats\n", "np.array([1.0,2,3,4,5])" @@ -134,9 +189,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1., 2., 3., 4., 5.])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# same as above\n", "np.array([1,2,3,4,5], dtype='float')" @@ -144,9 +210,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 2, 4, 6, 8, 10, 12, 14, 16, 18])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# spaced values in interval\n", "np.array([x for x in range(20) if x % 2 == 0])" @@ -154,9 +231,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0, 2, 4, 6, 8, 10, 12, 14, 16, 18])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# same as above\n", "np.arange(0,20,2)" @@ -164,9 +252,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.20907096, 0.36931203, 0.44534147, 0.6545148 , 0.55729317,\n", + " 0.23846956, 0.0998131 , 0.01546743, 0.91981562, 0.43352004])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# random floats in [0, 1)\n", "np.random.random(10)" @@ -174,9 +274,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([11, 9, 12, 5, 12, 7, 10, 13, 14, 9])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# random integers\n", "np.random.randint(5, 15, size=10)" @@ -191,7 +302,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -200,18 +311,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "10" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x[0]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 20])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# slice\n", "x[0:2]" @@ -219,18 +352,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 20, 30, 40, 50])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x[0:1000]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "50" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# last value\n", "x[-1]" @@ -238,9 +393,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([50])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# last value as array\n", "x[[-1]]" @@ -248,9 +414,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([30, 40, 50])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# last 3 values\n", "x[-3:]" @@ -258,9 +435,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 30, 50])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# pick indices\n", "x[[0,2,4]]" @@ -277,7 +465,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -287,9 +475,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 20, 30, 40, 50])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x2[0] = 10\n", "\n", @@ -298,9 +497,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 10, 10, 40, 50])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x2[[1,2]] = 10\n", "\n", @@ -309,9 +519,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 10, 10, 0, 1])" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x2[[3,4]] = [0, 1]\n", "\n", @@ -320,9 +541,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([10, 20, 30, 40, 50])" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# check if the original vector changed\n", "x" @@ -337,72 +569,161 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "150" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x.sum()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "30.0" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x.mean()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "50" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x.max()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "4" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x.argmax()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([2.30258509, 2.99573227, 3.40119738, 3.68887945, 3.91202301])" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.log(x)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([2.20264658e+04, 4.85165195e+08, 1.06864746e+13, 2.35385267e+17,\n", + " 5.18470553e+21])" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.exp(x)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 20, 40, 60, 80, 100])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x + x # Try also with *, -, /, etc." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([11, 21, 31, 41, 51])" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "x + 1" ] @@ -418,7 +739,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ @@ -429,9 +750,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1.13948279, 1.71442668, 1.2142152 , ..., 1.52286464, 1.83729564,\n", + " 1.71988707])" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# get random vector\n", "samp = np.random.random_sample(int(1e7))+1\n", @@ -440,18 +773,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 97.8 ms, sys: 16.5 ms, total: 114 ms\n", + "Wall time: 114 ms\n" + ] + } + ], "source": [ "%time _ = np.log(samp)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 11 s, sys: 135 ms, total: 11.1 s\n", + "Wall time: 11.2 s\n" + ] + } + ], "source": [ "%time _ = listlog(samp)" ] @@ -474,54 +825,130 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.array([[1,2,3], [4,5,6]])" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 2., 3.],\n", + " [4., 5., 6.]])" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.array([[1,2,3], [4,5,6]], dtype='float')" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0., 0., 0., 0., 0.],\n", + " [0., 0., 0., 0., 0.],\n", + " [0., 0., 0., 0., 0.]])" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.zeros((3,5))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 1., 1., 1., 1.],\n", + " [1., 1., 1., 1., 1.],\n", + " [1., 1., 1., 1., 1.]])" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.ones((3,5))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 0., 0.],\n", + " [0., 1., 0.],\n", + " [0., 0., 1.]])" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.identity(3)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 43, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 0, 0],\n", + " [0, 2, 0],\n", + " [0, 0, 3]])" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "np.diag([1,2,3])" ] @@ -535,9 +962,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 44, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X = np.array([[1,2,3], [4,5,6]])\n", "X" @@ -545,27 +984,60 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 45, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3])" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X[0]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 46, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "1" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X[0,0]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 47, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3])" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# get row\n", "X[0, : ]" @@ -573,9 +1045,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 4])" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# get column\n", "X[ : , 0]" @@ -583,9 +1066,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 3],\n", + " [4, 6]])" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# get multiple columns\n", "X[ : , [0,2]]" @@ -600,9 +1095,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# X2 = X # try this line instead\n", "X2 = X.copy()\n", @@ -612,9 +1119,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 51, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[20, 2, 3],\n", + " [ 4, 5, 6]])" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X2[0,0] = 20\n", "\n", @@ -623,9 +1142,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 52, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 3, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X2[0] = 3\n", "\n", @@ -634,9 +1165,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 53, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[3, 3, 5],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "X2[: , -1] = [5, 6]\n", "\n", @@ -645,9 +1188,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 54, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# check if original matrix changed\n", "X" @@ -662,9 +1217,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6])" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "z = np.arange(1, 7)\n", "\n", @@ -673,18 +1239,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 56, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(6,)" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "z.shape" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 57, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [4, 5, 6]])" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "Z = z.reshape(2,3)\n", "\n", @@ -693,27 +1282,60 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 58, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(2, 3)" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "Z.shape" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 59, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6])" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "Z.reshape(6)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 60, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([1, 2, 3, 4, 5, 6])" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# same as above\n", "Z.flatten()" @@ -721,9 +1343,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 61, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 4],\n", + " [2, 5],\n", + " [3, 6]])" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# transpose\n", "Z.T" @@ -738,9 +1373,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 62, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1., 2., 3.],\n", + " [4., 5., 6.]])" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "A = np.array(range(1,7), dtype='float').reshape(2,3)\n", "\n", @@ -749,7 +1396,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 63, "metadata": {}, "outputs": [], "source": [ @@ -758,9 +1405,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 64, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1., 4., 9.],\n", + " [ 4., 10., 18.]])" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# not the same as A.dot(B)\n", "A * B" @@ -768,27 +1427,62 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 65, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[2., 4., 6.],\n", + " [5., 7., 9.]])" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "A + B" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 66, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1. , 1. , 1. ],\n", + " [4. , 2.5, 2. ]])" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "A / B" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 67, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([14., 32.])" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# matrix multiplication\n", "A.dot(B)" @@ -796,27 +1490,63 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 68, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([14., 32.])" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "B.dot(A.T)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 69, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[14., 32.],\n", + " [32., 77.]])" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "A.dot(A.T)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 70, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[1, 2, 3],\n", + " [2, 4, 6],\n", + " [3, 6, 9]])" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# outer product\n", "# multiplying each element of first vector by each element of the second\n", @@ -865,9 +1595,7 @@ }, { "cell_type": "markdown", - "metadata": { - "collapsed": true - }, + "metadata": {}, "source": [ "## Going beyond NumPy alone\n", "\n", @@ -884,7 +1612,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 71, "metadata": {}, "outputs": [], "source": [ @@ -893,9 +1621,102 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " 0 1 2 3 4 5\n", + "gnarly 1.0 0.0 1.0 0.0 0.0 0.0\n", + "wicked 0.0 1.0 0.0 1.0 0.0 0.0\n", + "awesome 1.0 1.0 1.0 1.0 0.0 0.0\n", + "lame 0.0 0.0 0.0 0.0 1.0 1.0\n", + "terrible 0.0 0.0 0.0 0.0 0.0 1.0" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "count_df = pd.DataFrame(\n", " np.array([\n", @@ -919,7 +1740,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 73, "metadata": {}, "outputs": [], "source": [ @@ -931,9 +1752,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 74, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Dimensions of X: (150, 4)\n", + "\n", + "Dimensions of y: (150,)\n" + ] + } + ], "source": [ "iris = datasets.load_iris()\n", "X = iris.data\n", @@ -946,9 +1778,29 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "X_iris_train: \n", + "y_iris_train: \n", + "\n", + " precision recall f1-score support\n", + "\n", + " setosa 1.00 1.00 1.00 11\n", + " versicolor 1.00 0.74 0.85 19\n", + " virginica 0.75 1.00 0.86 15\n", + "\n", + " accuracy 0.89 45\n", + " macro avg 0.92 0.91 0.90 45\n", + "weighted avg 0.92 0.89 0.89 45\n", + "\n" + ] + } + ], "source": [ "# split data into train/test\n", "X_iris_train, X_iris_test, y_iris_train, y_iris_test = train_test_split(\n", @@ -959,8 +1811,8 @@ "\n", "# start up model\n", "maxent = LogisticRegression(\n", - " fit_intercept=True, \n", - " solver='liblinear', \n", + " fit_intercept=True,\n", + " solver='liblinear',\n", " multi_class='auto')\n", "\n", "# train on train set\n", @@ -986,7 +1838,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 76, "metadata": {}, "outputs": [], "source": [ @@ -997,9 +1849,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 77, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0.11932101822769925" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# cosine distance\n", "a = np.random.random(10)\n", @@ -1009,9 +1872,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 78, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(0.10357764286724046, 0.7758390819294883)" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# pearson correlation (coeff, p-value)\n", "pearsonr(a, b)" @@ -1019,9 +1893,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 79, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-1.48, 0.36, 0.88],\n", + " [ 0.56, 0.08, -0.36],\n", + " [ 0.16, -0.12, 0.04]])" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# inverse of matrix\n", "A = np.array([[1,3,5],[2,5,1],[2,3,8]])\n", @@ -1044,7 +1931,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 80, "metadata": {}, "outputs": [], "source": [ @@ -1053,9 +1940,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 81, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "a = np.sort(np.random.random(30))\n", "b = a**2\n", @@ -1085,9 +1985,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/tutorial_pytorch.ipynb b/tutorial_pytorch.ipynb index eb1a772..d0c3701 100644 --- a/tutorial_pytorch.ipynb +++ b/tutorial_pytorch.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Ignacio Cases\"\n", - "__version__ = \"CS224U, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -102,7 +102,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "PyTorch version 1.4.0\n", + "PyTorch version 1.8.0\n", "GPU-enabled installation? False\n" ] } @@ -223,8 +223,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor([[-1.2283e+27, 4.5884e-41, -1.2077e+24],\n", - " [ 4.5884e-41, -1.4031e+27, 4.5884e-41]])\n", + "tensor([[9.8091e-45, 0.0000e+00, 0.0000e+00],\n", + " [0.0000e+00, 0.0000e+00, 0.0000e+00]])\n", "torch.Size([2, 3])\n" ] } @@ -376,10 +376,10 @@ " [1., 1., 1.]])\n", "tensor([[5., 5., 5.],\n", " [5., 5., 5.]])\n", - "tensor([[0.5275, 0.1870, 0.5300],\n", - " [0.1604, 0.1122, 0.3216]])\n", - "tensor([[-0.3025, -1.6446, -0.1769],\n", - " [ 1.1837, -1.2383, -0.7167]])\n" + "tensor([[0.2930, 0.9685, 0.0458],\n", + " [0.9844, 0.1271, 0.2497]])\n", + "tensor([[-0.4341, 0.1566, -0.7059],\n", + " [ 0.5371, 0.0399, 0.5803]])\n" ] } ], @@ -410,12 +410,12 @@ "metadata": {}, "outputs": [], "source": [ - "# creates a new copy of the tensor that is still linked to \n", + "# creates a new copy of the tensor that is still linked to\n", "# the computational graph (see below)\n", "t1 = torch.clone(t)\n", "assert id(t) != id(t1), 'Functional methods create a new copy of the tensor'\n", "\n", - "# To create a new _independent_ copy, we do need to detach \n", + "# To create a new _independent_ copy, we do need to detach\n", "# from the graph\n", "t1 = torch.clone(t).detach()" ] @@ -517,7 +517,7 @@ { "data": { "text/plain": [ - "tensor([-0.2222, 0.4038])" + "tensor([-0.3105, -0.7634])" ] }, "execution_count": 14, @@ -548,14 +548,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor([[-0.9512, 0.0463, 0.6822, 0.4541, 0.1027, -0.2106],\n", - " [ 0.5921, -0.6410, 1.5878, -0.0321, -0.5603, 0.5489],\n", - " [ 1.0219, 1.5319, 1.5433, 1.1993, 1.7030, -1.4134],\n", - " [-0.8388, -0.4763, 1.1888, 0.7077, -0.2650, -0.1021],\n", - " [-1.0012, 0.9604, 1.0057, -0.9991, -0.7933, -0.7060]])\n", - "tensor([[ 0.5921, -0.6410, 1.5878, -0.0321, -0.5603, 0.5489],\n", - " [-0.8388, -0.4763, 1.1888, 0.7077, -0.2650, -0.1021]])\n", - "tensor([-0.5603, -0.1021])\n" + "tensor([[ 0.0421, 0.0713, -2.1790, 0.3855, 1.8714, -0.2528],\n", + " [-0.3344, 0.8028, -0.2878, -0.2721, 1.0514, -1.3336],\n", + " [-1.3506, 0.5657, 1.4540, -0.7039, -0.6878, 0.9614],\n", + " [ 0.3845, 0.4493, -0.8910, -1.4512, 0.1300, 1.5551],\n", + " [ 0.9192, 0.3812, -1.3167, 0.4005, -0.0778, 1.5110]])\n", + "tensor([[-0.3344, 0.8028, -0.2878, -0.2721, 1.0514, -1.3336],\n", + " [ 0.3845, 0.4493, -0.8910, -1.4512, 0.1300, 1.5551]])\n", + "tensor([1.0514, 1.5551])\n" ] } ], @@ -591,22 +591,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor([[-0.9512, 0.0463, 0.6822, 0.4541, 0.1027, -0.2106],\n", - " [ 0.5921, -0.6410, 1.5878, -0.0321, -0.5603, 0.5489],\n", - " [ 1.0219, 1.5319, 1.5433, 1.1993, 1.7030, -1.4134],\n", - " [-0.8388, -0.4763, 1.1888, 0.7077, -0.2650, -0.1021],\n", - " [-1.0012, 0.9604, 1.0057, -0.9991, -0.7933, -0.7060]])\n", - "tensor([[-0.9512, 0.0463, 0.6822, 0.4541, 0.1027, -0.2106],\n", - " [ 0.5921, -0.6410, 1.5878, -0.0321, -0.5603, 0.5489],\n", - " [ 1.0219, 1.5319, 1.5433, 1.1993, 1.7030, -1.4134],\n", - " [-0.8388, -0.4763, 1.1888, 0.7077, -0.2650, -0.1021],\n", - " [-1.0012, 0.9604, 1.0057, -0.9991, -0.7933, -0.7060]],\n", + "tensor([[ 0.0421, 0.0713, -2.1790, 0.3855, 1.8714, -0.2528],\n", + " [-0.3344, 0.8028, -0.2878, -0.2721, 1.0514, -1.3336],\n", + " [-1.3506, 0.5657, 1.4540, -0.7039, -0.6878, 0.9614],\n", + " [ 0.3845, 0.4493, -0.8910, -1.4512, 0.1300, 1.5551],\n", + " [ 0.9192, 0.3812, -1.3167, 0.4005, -0.0778, 1.5110]])\n", + "tensor([[ 0.0421, 0.0713, -2.1790, 0.3855, 1.8714, -0.2528],\n", + " [-0.3344, 0.8028, -0.2878, -0.2721, 1.0514, -1.3336],\n", + " [-1.3506, 0.5657, 1.4540, -0.7039, -0.6878, 0.9614],\n", + " [ 0.3845, 0.4493, -0.8910, -1.4512, 0.1300, 1.5551],\n", + " [ 0.9192, 0.3812, -1.3167, 0.4005, -0.0778, 1.5110]],\n", " dtype=torch.float64)\n", - "tensor([[ 0, 0, 0, 0, 0, 0],\n", - " [ 0, 0, 1, 0, 0, 0],\n", - " [ 1, 1, 1, 1, 1, 255],\n", - " [ 0, 0, 1, 0, 0, 0],\n", - " [255, 0, 1, 0, 0, 0]], dtype=torch.uint8)\n" + "tensor([[ 0, 0, 254, 0, 1, 0],\n", + " [ 0, 0, 0, 0, 1, 255],\n", + " [255, 0, 1, 0, 0, 0],\n", + " [ 0, 0, 0, 255, 0, 1],\n", + " [ 0, 0, 255, 0, 0, 1]], dtype=torch.uint8)\n" ] } ], @@ -647,7 +647,7 @@ } ], "source": [ - "# Scalars =: creates a tensor with a scalar \n", + "# Scalars =: creates a tensor with a scalar\n", "# (zero-th order tensor, i.e. just a number)\n", "s = torch.tensor(42)\n", "print(s)" @@ -697,17 +697,17 @@ "output_type": "stream", "text": [ "Row vector\n", - "tensor([[ 2.4337, -1.6546, 1.7862]])\n", + "tensor([[ 1.5811, -0.0148, -2.1993]])\n", "with size torch.Size([1, 3])\n", "Column vector\n", - "tensor([[-0.8834],\n", - " [-0.3613],\n", - " [-1.4556]])\n", + "tensor([[-0.5085],\n", + " [ 1.1261],\n", + " [ 0.2023]])\n", "with size torch.Size([3, 1])\n", "Matrix\n", - "tensor([[ 0.4256, 0.5723, -0.4221],\n", - " [-1.2646, 0.8962, 0.9930],\n", - " [ 0.4961, -0.4934, -2.6406]])\n", + "tensor([[-1.6138, 0.5316, -0.6007],\n", + " [ 0.8608, -0.9427, 0.0111],\n", + " [-0.7028, -1.2223, 1.1992]])\n", "with size torch.Size([3, 3])\n" ] } @@ -742,12 +742,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor([[ 0.0317],\n", - " [-0.6520],\n", - " [ 3.5837]])\n", - "tensor([[ 0.0774],\n", - " [-1.1959],\n", - " [ 3.1463]])\n" + "tensor([[ 1.2978],\n", + " [-1.4971],\n", + " [-0.7765]])\n", + "tensor([[ 0.6784],\n", + " [-2.1156],\n", + " [ 0.5897]])\n" ] } ], @@ -775,7 +775,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "7.557076454162598\n" + "3.781867027282715\n" ] } ], @@ -809,10 +809,10 @@ } ], "source": [ - "# common tensor methods (they also have the counterpart in \n", + "# common tensor methods (they also have the counterpart in\n", "# the torch package, e.g. as torch.sum(t))\n", "t = torch.randn(2,3)\n", - "t.sum(dim=0) \n", + "t.sum(dim=0)\n", "t.t() # transpose\n", "t.numel() # number of elements in tensor\n", "t.nonzero() # indices of non-zero elements\n", @@ -892,8 +892,8 @@ "except AssertionError as err:\n", " print(err)\n", " t_gpu = None\n", - " \n", - "t_gpu " + "\n", + "t_gpu" ] }, { @@ -912,9 +912,9 @@ { "data": { "text/plain": [ - "tensor([[-0.4632, -1.7737, 0.5267],\n", - " [ 1.1636, -0.3238, -0.1688],\n", - " [ 1.4534, 2.6819, -0.0517]])" + "tensor([[-0.2433, 1.0280, 1.5176],\n", + " [-1.7238, -0.6753, -2.9171],\n", + " [-1.1786, 0.0207, 0.3460]])" ] }, "execution_count": 25, @@ -923,9 +923,9 @@ } ], "source": [ - "# we could also state explicitly the device to be the \n", + "# we could also state explicitly the device to be the\n", "# CPU with torch.randn(3,3,device=\"cpu\")\n", - "t = torch.randn(3, 3) \n", + "t = torch.randn(3, 3)\n", "t" ] }, @@ -952,13 +952,13 @@ "source": [ "try:\n", " t_gpu = t.to(\"cuda:0\") # copies the tensor from CPU to GPU\n", - " # note that if we do now t_to_gpu.to(\"cuda:0\") it will \n", - " # return the same tensor without doing anything else \n", + " # note that if we do now t_to_gpu.to(\"cuda:0\") it will\n", + " # return the same tensor without doing anything else\n", " # as this tensor already resides on the GPU\n", " print(t_gpu)\n", " print(t_gpu.device)\n", "except AssertionError as err:\n", - " print(err) " + " print(err)" ] }, { @@ -1001,9 +1001,9 @@ { "data": { "text/plain": [ - "tensor([[-0.4632, -1.7737, 0.5267],\n", - " [ 1.1636, -0.3238, -0.1688],\n", - " [ 1.4534, 2.6819, -0.0517]])" + "tensor([[-0.2433, 1.0280, 1.5176],\n", + " [-1.7238, -0.6753, -2.9171],\n", + " [-1.1786, 0.0207, 0.3460]])" ] }, "execution_count": 28, @@ -1012,7 +1012,7 @@ } ], "source": [ - "# moves t to the device (this code will **not** fail if the \n", + "# moves t to the device (this code will **not** fail if the\n", "# local machine has not access to a GPU)\n", "t.to(device)" ] @@ -1133,12 +1133,12 @@ " # call super to initialize the class above in the hierarchy\n", " super(MyCustomModule, self).__init__()\n", " # first affine transformation\n", - " self.W = nn.Linear(n_inputs, n_hidden) \n", + " self.W = nn.Linear(n_inputs, n_hidden)\n", " # non-linearity (here it is also a layer!)\n", " self.f = nn.ReLU()\n", " # final affine transformation\n", - " self.U = nn.Linear(n_hidden, n_output_classes) \n", - " \n", + " self.U = nn.Linear(n_hidden, n_output_classes)\n", + "\n", " def forward(self, x):\n", " y = self.U(self.f(self.W(x)))\n", " return y" @@ -1160,7 +1160,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor([[-0.0939, 0.1568]], grad_fn=)\n" + "tensor([[0.2473, 0.1775]], grad_fn=)\n" ] } ], @@ -1173,10 +1173,10 @@ "# instantiate the model\n", "model = MyCustomModule(n_inputs, n_hidden, n_output_classes)\n", "\n", - "# create a simple input tensor \n", - "# size is [1,3]: a mini-batch of one example, \n", + "# create a simple input tensor\n", + "# size is [1,3]: a mini-batch of one example,\n", "# this example having dimension 3\n", - "x = torch.FloatTensor([[0.3, 0.8, -0.4]]) \n", + "x = torch.FloatTensor([[0.3, 0.8, -0.4]])\n", "\n", "# compute the model output by **applying** the input to the module\n", "y = model(x)\n", @@ -1226,7 +1226,7 @@ " nn.Linear(n_inputs, n_hidden),\n", " nn.ReLU(),\n", " nn.Linear(n_hidden, n_output_classes))\n", - " \n", + "\n", " def forward(self, x):\n", " y = self.network(x)\n", " return y" @@ -1254,13 +1254,13 @@ " nn.ReLU(),\n", " nn.Linear(n_hidden, 2*n_hidden),\n", " nn.ReLU(),\n", - " nn.Linear(2*n_hidden, n_output_classes), \n", + " nn.Linear(2*n_hidden, n_output_classes),\n", " # dropout argument is probability of dropping\n", " nn.Dropout(1 - self.p_keep),\n", " # applies softmax in the data dimension\n", - " nn.Softmax(dim=1) \n", + " nn.Softmax(dim=1)\n", " )\n", - " \n", + "\n", " def forward(self, x):\n", " y = self.network(x)\n", " return y" @@ -1325,30 +1325,30 @@ "name": "stdout", "output_type": "stream", "text": [ - "tensor(0.5756, grad_fn=)\n" + "tensor(0.7287, grad_fn=)\n" ] } ], "source": [ - "# the true label (in this case, 2) from our dataset wrapped \n", + "# the true label (in this case, 2) from our dataset wrapped\n", "# as a tensor of minibatch size of 1\n", - "y_gold = torch.tensor([1]) \n", - " \n", - "# our simple classification criterion for this simple example \n", - "criterion = nn.CrossEntropyLoss() \n", + "y_gold = torch.tensor([1])\n", + "\n", + "# our simple classification criterion for this simple example\n", + "criterion = nn.CrossEntropyLoss()\n", "\n", "# forward pass of our model (remember, using apply instead of forward)\n", - "y = model(x) \n", + "y = model(x)\n", "\n", "# apply the criterion to get the loss corresponding to the pair (x, y)\n", "# with respect to the real y (y_gold)\n", - "loss = criterion(y, y_gold) \n", - " \n", + "loss = criterion(y, y_gold)\n", + "\n", "\n", "# the loss contains a gradient function that we can use to compute\n", - "# the gradient dL/dw (gradient with respect to the parameters \n", + "# the gradient dL/dw (gradient with respect to the parameters\n", "# for a given fixed input)\n", - "print(loss) " + "print(loss)" ] }, { @@ -1451,7 +1451,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1539,7 +1539,7 @@ " nn.Linear(5, 5),\n", " nn.ReLU(),\n", " nn.Linear(5, 1))\n", - " \n", + "\n", " def forward(self, x):\n", " return self.network(x)" ] @@ -1551,7 +1551,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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cNLg9usruNfaFeiNrfY7bE023zo/hfjJAmC6ENc/8niUfvVsf4SpKs6cSfj1KT0/n+eefx/nJv8BXed7+0MNr2VbwFU5fGVJKnL4yNhUvpaR8P/kkkeD28bfQSG4e3K7+g78Ef5nWkxe7bCRcO/tB5TCV1No2VFdIawTLSm4kc0wK1vZO9i2Yy4G1K+srXEVptlTCryfp6eksXLgQk9zM00mGWpf7Si51YD+wmg9LP+aTE//go9KP2WsuZ/TuQ3zA9bwc/tsml+zPmHjrP7g7fyIGLbgq1+Y2i/Dpai6qbsDNkNAPaO3JY9bx18gt7M6yUVOQCNa8/VpDhK0ozYpK+PVk+fLllMdkonlHkHagErex9ssnoT7J67c8xKt3PErrMB23LF9JYVQkIEjp0LRLD8yc+FPuz7sdvHaOxWxjd9sP0RsKAI1QXT5jwl+hk20tADbNw2Mn3mClcTz7O6bhcNR+A5qiKD+cumhbT8rKyvBETif5yAoynMc4mBBFz8wCDN+5DyKg05HV5nqemptDr7x3sR9Ix20y8do1N/HHpAISE6b+8AOmz4XlTzeq1aVC+sRxA7dS/HlvJn52HxFt1hDbazFGW4AzFZWd/lGU++8gQAwGdyETc3ysGTaWvvu3szhjMbN3zCbXmUtCSAL3972fSSmTGvScFKUpUQm/noyu7Ev0IcFSxwEEGjlRYQB0zi3G6vPjMhrZ3a8fOlsXOuz/hPDcdEpDQnlpxh3sHzqYrl1qvY+idulzg6tJ+aoWGWlEq0uF9InjI1c8fb6NQncKyk/Z6DAlD1NIAKd/FKX+XyOrSiwHiOOP+zz8pVsYHQqLeWLDLNwBNwA5zhxmbZgFoJK+ovxAakinHhx46s+UxzxMhGYEzs7CyYkKY1W3tnzdqwOrurWhtG0CN8f/Cr03g7/edR/X/vO/bBg8gj+mplzcAZc/fTbZn+FzBbf/QIszFjPhswmkvZvGhM8msDhj8cXF8D0eTUnk7Wtn4DYFp2UW7A5D8wvK/XdUJ/szrBr86qibilBLdbI/wx1wM3vH7DqLS1GaO9XDv4zm78wi5PPXibS+ygCPnwTLFNBdHaxrfy5dGOPESg7EPMDD/7yKLI+PVmYjj6Yk1lig5Acpy7y47edYnLGYWef0pp9Y/wTPbH6Gcm/5JQ+nTE+Igjtv41Xp56aF85GnCqmwQmjXmFrbx7sFusxS7vgygnevKa2xL9eZ+6NiUJSWSCX8y2T+ziwqX3mOqxPfY3bZdPItbbEJP5WpBrzF5bQp2P+d1gaMlv4ktBpM/E/v55KrB9lbBYdxatv+A8zeMfu83rRP81HmDS5FWBfDKdMTopj+6O9InzSev6zdjMG1mQdKS4nzn//hVmZwYPP5ufJgEfHFSXw6voLjycFprQkhjeNGM0VpCtSQzmWy8917GXlqPrPd11NmbUWIzo8QEKLzExYdwqm4HsGGujD01jEsGdKX+J/eXzcHH/ckGK01txmtwe0/wA/pNdfVcEpaWhoPtu6KRfRglWUPblFzqqZX+FmlD2P94Kc5mNyDsig9I3fHMHNZWzrlRHB/3zp6zxSlBVAJ/zJ4ddWrTF1/guM9n6LA0g6DqDnr3iAkpshQLBEPoouYjmtgOrekta+7ANJmwJQXwN4aEMGvU174wRdsf2ivua6GUwZcM5yJfeJoWx7FBsMRKnAhkRQaAiw2G0hMX0/S0Zc5bXfgMRgRCCxeGLQ7gpQsW53EoCgtgUr4l8E7x94mc9Tf6WI6iU2cX7IYwCb8vD/0t7iufBJ/eMe6v6EqbQY8uBdmlQa/XsTsnPv73o9FX3sht++qy+GU6WNvptPK9+hWpiNXV8KS/DzWF2ok7l5Pl0MfcTTZhqar+eOq1ySL3nylzmJQlOZOjeFfBl0qf88A41aijS9hF7dSRvh5bSqlgd/GGNl5fBTP/OrRBojyws6My5+Z824323F4Hfjl2aUWLXpLnQ+ntHnycTIffYyKqN54ut0JQErGl2SnRXIwwcmOzmU4rQFCXHr6HoqgQ04owuX6/hdVFKWaSvi1+KE3+BzenMvGBcdwFHsIjTIzZGoHnsx/mO2p9xJb8Ag64WEc61jIeHwYq5/nl4Jir+C13bfj1vWoz1P7wSalTKpxzvVx09OZWv3i7/9gp7kEsycKi6eEkl5uYp3h/GWXjgHReYQbPTjDbCzS9eF4vrlOY1CU5kyteHWOc6ckQrA3O2vorBoJ7vDmXFZ+eBC/92zFy7BW8/jCmEjRgHasWf1LRNXYfTqdWc5wygjDLis4UWFkSepoRLbgmet6qiX9avHM258RsjWU4euf5tspDtLyTFyRdBTjd66H+NHxbdHNrGgfwXO//WsDRqsojcf3rXilEv45Jnw2gRxnznnbE0MSWXr90urH5y4p6Pcc4Ko+X/CKawChLgsGKbGLCsaxjjQOVbdzapF8YPkF7+kG8vDEzirZf49n3v6MDvPTKQrbwK0ddhEmfOe10RD8MSqa8Njf8MhN9zfKkhKKUp/UEocX4UIzT87dfu76sR2Nn5CR05qISmtwnEwIyghnIeNJpzMAAc3AAl0iabvzWf+IWqz7f3n0ruvhqoVU+syE1pLsAXRInigpwpn3Xz7f8nWwhETZaUCeLSmRPrd+A1eURkol/HNcaObJudvPLCUIkGpZTUn7RHaExcE5UzB9GFkuh+N16sneFMqWij8QeXhz3QfeTBnbOgkxeHGbL/yjapWSeyuyeWaLl88jhtbceZElJRSlOVMJ/xy1TUmsbUbKmUXDUy2rOdxjFQkDt+H1nnOzU5Uywji2MJ5jxcmkpn+Bpf8Nly3+5iY3dBilHdpyKCGUwPf8tCYGAvTcuIt/aTedv/MHlpRQlOZOJfxzTEqZxKyhs0gMSUQgSAxJPO+CLZxdNHxbt7X0Kcgm/gkjNuf5q1gB2Cor8RoM5FtiuDqxF7G/vLk+TqVZuHfE27h1yWx2dGJ/ShjaBdr5ieaXI49wVcFCJrRKIq1daya0SmJxiO0Hl5RQlOZOTcusxblTEi/Ebc1nYH4hEXP16LyCtN3pbB04gIDh7Nuq9/vpcOgge3qNZFzPOwif2I6QPnGXM/xmx2oIYbO7LYcCHm5NyaLXiWL038n8mjRT7ruT+JNDmdD5HVIMFp71+8kxGpgVEw3tr0UVUFYU1cP/0dLT01n7/nziF3vReYOrd7Q9dYoBW7ZiczpBSkymSg56O/NYl5+Q9oefk/jIQJXsa5M+F57vAbMigl/Puch61TVX0sbRltL8TtwvQtl5sC8+LRYpQUodQngICZ1Nec87cMceICbWydUVDgDcOsHsQnXNRFFAJfwfbdGiL3CfykJ/zlrcbU+dYsrCRcz45BPy2kazQWfnLquOtLS0hgm0sTuzWMv3zKxJS0ujTb/RdCqIYWZZH3aZfkm5/3YkZoTQEIDF66frEQfRZbno9QF+Is/WJlIllBUlSCX8H2nA/lVYvCfwWPW17ndGWphf0Jvptjx+PW1IPUfXhFxgsZbcLx5j/s6s6k0/uWYUA1r3YOSrO/CYowg3vIfunDpFeg06nKhECDjd7RQPGNrhtg1RJZQVpYoaw/8Rlv9xGu32Z5PeMZUDMTGkZeejD5zdH9DDokG3Msu3kRlTfqmGcb7PBWbQxMlCHv1iD0D1/Qrjfn0776V/jdvgwyAKa7Q/XDmCjY5bcWgxGAqKie05j/atdnGdLgmn9uvLew6K0kSoHv5F+s/DDzBQvw5/pQ6Lz09OVBjpSXFUGg1IoNJoYEubNvzMmEKnoctVsv9fLjCDJltG4/IFeG7JoRrbbRN9rOhlo0KLrt52uHIEK8t/iUOLA3T4K2PI3XY7pZm9GSOXscynbnBTFKijhC+EuFIIcUgIcVQI8Ugt+0cLIcqEELuq/v2wlTgamay5s0jX9nCqPIKV3driNhpAyhpr067p0gZ3u6upTPmMlA4PNXTIjV8ti7VUShP/8AfLIWSX1hzuGTb8NtqGrubl2LvwyeCauBsdt+I/Zy1cGTBTsOdaDAJ8le9dxhNQlKbjkhO+EEIPvAxcBXQDbhJCdKul6VopZe+qf03v1sf0uWw9+TpZkQ6+zUnFZTSCEMF/wekiWLw+/MZYRp7YRdi1N5KYMLWho278qhZrySUWTQoytRge8f2UL7XhACRF1PwwSEyYyhNj08hvVc7vUn/LaXM8Dq32tXB9ldFsyunH1aXZl/00FKUpqIse/kDgqJQyQ0rpBeYAzS7TVX79JAdTejLmeBQBec6FWiGw+v10smt0K85lZ+dMlewvRtoMNk1dTXdtDsO9L1Qne6tRz8MTO5/XPDFhKuNMI/k06UoGDJ5Lqa32S1FlVh1vFP+UEL0N5878y3oKitIU1EXCTwa+u2J2ZtW2cw0RQuwWQnwthOh+oRcTQtwjhNgmhNhWUFBQB+HVjTkprUiLOEXAUftb5jIaKQ4zkJQYRcY1t9dzdE3ftD7JPHNdT5IjrAggOcL6vaWjJ0+eTJgnWFBtRZoV73c+g8NabyJl0h8YNPmnvJLyOH5Pe+at/rgezkJRGre6mKUjatl2bs3lHUBbKaVDCHE1MB9Ire3FpJSvA69DsDxyHcR3yTYs+hfhUaWYhRdjqA+fw3ReG4dFY17ba+gc9hlPjb2tAaJs+qb1Sb6oCqL3Rpv4Z4WXfW2DhewmbneSkLCJxAHvozMEF0M324qZmDKHrEOj+NOOT3iq742XJXZFaQrqooefCbT+zuNWQI1BUylluZTSUfX9V4BRCFH7wGsjs2HRv3h3wSkiCN5hlTiwAGGoWdFFAhsTOvHggfk89fPlDRBly/TgwN48VLCHcL+bfW1M+Iw64tLmVSf7M3QGL/Htt5O/9BB/2vFJA0WrKA2vLhL+ViBVCNFeCGECZgJffreBECJBCCGqvh9YddyiOjj2ZffB4hOUd4ugJBAcM4hKLaf1yByMoV5Aog/xIYUek2UyJ659sGGDbYEenHk321f/g+1LC7FXahhsxbW2M1qL+fU7HzP2589QtnBhPUepKI3DJSd8KaUf+BWwBDgAzJVS7hNC/EII8YuqZtcDe4UQu4EXgJmyMS+19R3lqXbu7PERi8p0nFnNMCq1nO63HKPbzw6y88qT+EOTmZ6ocePkKxs22BYqbMZM7OIlvBY3/sqoWtt4XVEIIK7CQ84TT6qkr7RIaonD71Gy9g/scn6KZhJICc6qhB+ig5KAYFGZgV2OKJKO3cjXf7n/+19MuayOTErlwDV9KS7qRXL/92sM62h+E1/tvYmOiw8yNmsnADImhm7r1jZUuIpy2aglDn+M9LnkHH8fzRh8KASE6sEk4P1iI0/nWNnuCsFReQ1DAnkNG6vCq0l3U1S4j/3lVk7uvA2vMwopweOMYvHum5iX348X+tzAiuQ+wScUFpKent6wQStKPVO1dC7gxPrfkdPJet4cJJMOJtv9bHUn4Cm/kn6nW/Hks7c2TJBKtZG/vI23vprHyOPL2ahPY/m2p8BT869Xj8HEu92vYmzWToQ1iqVL96kqpkqLonr4tVi86glOtgupfcIpEKmX2HbfzZQ9On7SV31mNgbT+iTjjAlHpw+j29F08NS+NlaBNZKAEOyMMWDd+SXps/9Uz5EqSsNRCb8Wuq0G/CbfBfeXEskbK//FtX0ruXLGzHqMTPk+zw/5F+VtLCAMhOCptU2o38Fng3uxtUs33P4Klm3cyq4PFtRzpIrSMFTCP8exzw7TvqI3Bnd0rfsl8JG4jYMD2jDqnln1Gpvy/dLS0ug/fDppDhtDHXvQE6ixX8abcIxuxX9u+z2Lxt/Iur6jkVLH2q8+aKCIFaV+qYR/jk8Ov4/NG0nMkemIwDl31Er4lokcq+zNzP98WfsLKA1q8uTJlEZ1oH/2XBLDlxEq3SAlIk6Pp0c0rtBQEIKKsAi29h3F/o5peAMuVWtHaRFa9AD0gbUrWTvnPSqKCgmLjmHEzNv5Mm4pE8rHkpA7FIDC1M/xW4owuKMxHLmOOd3HMnXrKpg8qmGDVy4o3zaG4du/QrCMYfu/5d9DJ7Jo1K1gqNm/8RuMrB92Bd2OplP6xREAtX6B0qy12IR/YO1Klr7+En5vcKy3orCANz99F2ffSv6Dlz+gx547FHtV4nch+TsuJhV9w6Q+YxoydOV/CI0yc6TTDQw9+BHFIVY2RA9BWmpfirLUEkF0x0qkT6Nw4WGV8JVmrcUm/LVz3qtO9m1CunIwsoBPetxFIPl2lp7wgtvFL7AQhyAfyX9ws9NVyFMpg5h43YgGjl75PkOmdmClw8dBYLHVi1MXAu4AWM//cY+hkLhRBbACRKVGenq6mqqpNFstNuFXFAXXRG0T0pW4tnkciBvPFyd1xB/S8ZkBXhIulgXrvQFg0LxMsB5j8j23NFTIyg/UaVBw0fKNC4xs0fKIqywh+7ANXZoNrzi7MpZJupnBh5j0lQAUGEr47dpvWa0SvtJMtdiLtmHRwWKdaZGjiDFr3HkymUR38A2Z4TfyB2nBbNQhgTB/KdeUbeXqaW0aNGblh+s0KIE7/jaM4eHF3L5/CSGZZdzofZ8YmQ9SI0bm81NeZRjrQIBbeHgnbj5F5pUNHbqiXDYtNuGPmHk7BpOZvNYPo+0vpXzlLymf/zNKV/6Mkux/MQkTn8hQPBOSeLP4z/RI3MLkwXc2dNjKRbpv8kB84af5zb65FGaW8Jx2Lx9yA7O5l2Gsw6vBSYcVPwE6+yMQhjJyctW8fKV5arEJv+uIMVhvGkT8rkp0O4+iLxMIBPoygW7nQUqy/0W0TyKkZJ27M0PGPd7QISs/QlpaGpbfzCRM5+e4P505JUaK/cFieMV+wZwSIx8UhhIqbUzKn8p9hePJ2PU7SJ/b0KErSp1rsWP4AN/sXsTgg1aMvpo1FHQ+gXb4IK54mFixl6vufYCuI9TMnKbq3tH38hdLEUUHD1JUaWRHpbHGfqFzAmBEz+iiicz3LiJ34xdMh+Ai64rSTLTYHv6Sj96lR2YHDKW179eXwu6Al7TCQyrZNwN/HPxHbEZbrftifWdr6IdIK69vfpLnKibz+fZv6ys8RakXLTbhB1a8zLKwUVRG1L6/MgISpJcrBqo1UJuLJ4c8iVHUnI9v1kzcUXBN9eN8Qwm6kBPkFkTw9pYOvP6zGzmwVl3IVZqHFjmks+C5Zxkdd4JsLYZ3Ruq4+yuJxX92v9sA74zU0SlyF79Ju7rhAlXq1CSHEwpLeDQyHCkg1h/JVQWjyHf7eMO8nBBpplLvwRy7HH95H/bae5CUn4vrP/8GUH/pKU1ei+vhly1cSHqFk1fM93KHeRuru+l57WpBQThoQEE4vHa1YHU3Pb959LGGDlepS8ufZlJ5KfcWGjFoMCprLG63EYfOTU9xgJ/pXuZJ7XlWZx3jGt06QLAhajB+f4C1c95r6OgV5ZK1uB7+jm+WEIiNIiAFQoDVb2V9dxfru9dsF+pucZ+FzV9ZJgD3Oo8BHcj3G0k+fZTRReto16sAnUGCgBic/N38KnrdSeY5bgaCpTcUpalrcVltY3wIhrISQo6kE3pgG9euTqBDZmiNNoYAXJn6UANFqFw29lbV397rPEbr00cZsHUrrboUBZP9d1il5GGWEGbfTJfwfISuxf2qKM1Qi/opfurVz9BKnFhyTqLzexGAyasxbG80nU9FICRE+yJJC/0lfxp7W0OHq9S1cU+C0Vr9MC19D4ZAAKMtUGvzhIAfGb+EkPgrkFrtK2gpSlPS7BN+Tu4C1q8fwe9fvo91e09hKchEyJq/vDoNBh+M4/PDr/Bo4SjenXFvA0WrXFZpM2DKC2BvDQhslcH5977K2itp5ur1CL2L+a7NmFt1593H1nN4c249BqwodatZJ/yc3AUcPPg4bk82x7PbM1n/DcJX+9KFwu/hZMQ3DBzmrecolXqVNgMe3AuzSimMCtZTKtgdhuavefOd5heUbQtj2P4A2zqV48/az5GSb1j23n6V9JUmq1kn/Ixj/yQksxc911xHX9sGAkUGLrQyucXipTB5G5Ej/l6/QSoNxnPvfbhNJspP2cjZYsfr1CMleJ16crbY4ZCNn38l6XHMSVhKKVbHDvLEJ6yZe6ihQ1eUH6XZzdJJT09n+fLllJWV0aV1OwYeu4MN8X/GsDMc6a/98y2g17G9W3d+3bZPPUerNKTxt83kW8D4yktopwQlp23oa167xeKHW1dLKv+cA6vgxY4bmboDQK14pjQ9zaqHn56ezsKFCykrK+NUyCnCd/fi82Mv8ln4KIRLXuBZkm5hOXj7xdNn+O31Gq/S8MbfNpMDI59h0uz/Ir7zI3KyTRsWTpnMil8NoPxJPTq9pO3YbHqFefls0AFeXpfRcEEryo/UrBL+8uXL8VWN0evKCjiYt5qDHbuz9uQQKvShtT7HGKLxzejpXNvjnvoMVWlExl2XittoI79qTP9kmzZsHTiAkHZ5pHbehNnqQggQOpgZ6aO/JZ9nXWUq6StNTrNK+GVlZdXfdzsqCHdUsnbQeHBrbIgchE/UHMHyCQO2qHZ06HAl0xOizn05pYXoNCiBeJ2eN6beiMdgIL1XGgGDgXbtd6HX15yyadLBZLuGzyB4tTwXnu8BsyKCX1VJZaWRa1YJ3263V3+fUFSGO9xIeWgE0qLnSFgnlkePolwfigTK9aFsih1MhaMPDw7s3WAxK43Dk11asarvILa3T6bSFqyqaTY7a20bqQ8wVK6hyGKBstOADH5d+BuV9JVGrVldtB03bhwLFy7E5/NhbB+Gp0wS7ijFkRqGcV8ZR8I6cSSsU7CxDqaUVjDprtENGbLSSExPiOKLzz+nxGZA79MImPQ4feGEmsrPa1tINH2P7cbe9pwPBJ8Llj+taugrjVaz6uGnpaUxZcoUhhZF0ieqnJ+lHuCZ0y9hitfj625Hs+iRgDTr6GKzct3guOoFrxWlv9eB0IVhcbQHTccccTMezDXaeDAzV9xCSe4k2h87xr8ODOf1IwM4UBYbbFBVr0dRGqNm1cMHqHxrHes66Hgo9QnyrTGEO0rpeXAbJ9t3Jn9kPOGOMkbuziM7vg1jbh/S0OEqjci4ceP4+mghIZ626MqtrDR2wYOZGXxINEUUEc1cbmEDI5gQ5iTu5EwCIUs45TzA0pwuAHRtY2ngs1CUC2tWCf+buXM42MPAu2374TEEe2blYZHs7DSQq1d/wS8qvmGzcybm+HJcXQc0cLRKY5OWlgY/h9WvnMbijsfqkWywjGQDI89r+2yPEH5LgMkyuF7CKecB1uR3oetdamqv0ng1qyGd8n3v8N+UdtXJ/gy/0cSqQRPZVhTD0MiPGWz9mPuGpzRQlEpjlpaWxsS7+mEw6Zi4sxJ9oPb7N9x6wVudwlhn30HnuPEAOPyo8XulUWtWCT+q1ymKiK11X3loBBV+MxZ7EQWDflLPkSlNSadBCYy5pQvtcnOZssVBWGUApCSmpJhH33qRjx//NeO2rCPPIjgU9h92hqdzun0SNn14Q4euKN+rWQ3pYPcQ7gpQbjv/tMIdpWCE3EE/Z9SEJ+o/NqVJ6TQogQ+OvIAIlDB+x2387NMPsXjPFtZ75J1XGLduEf06Sr5s+w7rK39P/zBHA0asKP9bnfTwhRBXCiEOCSGOCiEeqWW/EEK8ULU/XQjRty6Oey6nDGXsbhcGf82bZQw+LyM3LyMh+YRK9soPdlW7q5HCxG0LayZ7AIOU9DqRxcqcHow9eju9fPG4Yrczf2dWA0WrNGWHN+fy7mPrefkXKy5rGe5LTvhCCD3wMnAV0A24SQjR7ZxmVwGpVf/uAV691OPWRtNB68IAk7e6CHe4QUrCK0qYuOYbOhQmc53FdTkOqzRTzw1/hKtSbiC8vPaS2Vafn4D0k168i0ewEJEXyYn5T9ZzlEpTd3hzLsve24+j2AOAo9hz2cpw18WQzkDgqJQyA0AIMQeYCuz/TpupwHtSSglsEkJECCESpZQ5dXD8amHSwcoeZiZtd9HzlBeoBMCrH87iQVYe7f9sXR5OaQGeG/4IeyLeQVd6flltlzH46+MMlPHzjk8yLX8SB0/Xvt6ColzImrmHkOcsuiYDwe11fZ9QXQzpJAOnv/M4s2rbxbYBQAhxjxBimxBiW0HBxS0c7XOaiYhYz6L+NkptOiRQatOxqL+NaMNeNYNC+VEqpgbQTDVn6yxr1Ze7r3iUF9v9grdb30qmqw3vJs1hZesYfvvIOw0TqNIkeZy1L7F5oe2Xoi4Sfm0ripw7l+2HtAlulPJ1KWV/KWX/2NjaZ9xcSMK3Yfw89DUi7et4aVIYf5kRyUuTwohxbeCT2392Ua+lKGfIkQmU3RzAGxb8of2mbX9e6HMDpWY7CIHTEI4n5zoqKrpjiFvKskAs8/70ZkOHrTR5Fyrp/uPVxZBOJtD6O49bAdk/os0lS5nwR7Q5j/Crq17lXl5FXwRhX1voeK0aylF+vJQOD3HQ9ziugS7+eugBCo7F4dMbAWivK6SfIYsQ4cVZ1Jl9sYUc0EFurirZofwwlhADbqf/vO1uQyWLMxYzKWVSnR2rLnr4W4FUIUR7IYQJmAl8eU6bL4Hbq2brDAbK6nr8HsA+ZQodr32W5FfbkfQrM8mvtqPjtc9inzKlrg+ltCCJCVPp0uWveJ1RZLZyUaEPAYLJfpjxJKE6L0JAqPAztGAwvwg5hCZUiQXlf1ucsZh17T4nIGom/IDws67d58zeMbtOj3fJPXwppV8I8StgCaAH3pJS7hNC/KJq/3+Ar4CrgaMEr6TedanHvRD7lCkqwSt1LjFhKp8vMeOfZCbWlUmBLYp+puPn/QIFhMQS8NA5IYPFK39P365PkpgwtUFiVhq3xRmLWfL649y1woPfUsyxDlPxmiLRNAcB1xoG7Sxho/f8aq2Xok5uvJJSfkUwqX9323++870E7quLYylKQ+kyOopKs5GfnvyYtwa2IcQnqe3ylBMPrbQYsrRS9u3/LaWl2+na5en6D1hp1Na99TfuXujDFADKt5HROpKi5Hg0vQ9dIApzYReG7ZHs+mABvW+tm05DsyqtoCiX0xXXD8Tq9rNvaBrmuCVU6itrbSf8XgqK8thWqUcA2dkfkZO7oH6DVRq9Kd84MAU0AEqGteX6jl/whOEfPCDeoLshHVdcCNLelRXf1t2iOirhK8pFmBkVxYp+QxDGUvZG7gXtnKlzWgBTfia7S1cxr9RUtVGSceyf9R6r0rhFOII39IW3qcTSqpS3xQye4gHeZgbtOUlP3T78sXY0d9n/eKUfTiV8RbkIzwzuQJ9jJ5FEkhmWiTnnBMLrASkRXg/mnJOYyotx+x04Ndjm1APgcmfz+n13cWDtygY+A6UxOLB2JS6jgZwBvcka3IGvxTjKCAcEZYTzNeNIJgefzktsdL86O65K+IpykZ4d0pGJp0aBBK+3gNBjewg7uJ3QY3swlRcD4LT4AcHisuD0TZ/DQEVhAUtff0kl/RbuxVXrmFoi+PTu+9GiU1gveuPDWKONDyMb6Q9AVFSXOjt286qWqSj1IC0tjRE7/s0mj2R75xKG7YnGoJ3tO/l1Grs7lpB6WuNIa4HmE2Rvjgvu83pYO+c9uo4Y01DhK/Xo89xinsnIIcvjI9lsZFhZLl8Y7OjEZiZuWkurwztIqtRTabORnpbGqXZtq59bRhgIOKg7QV3NO1QJX1F+hMFXTuWa148wN7mU9UC/Q5GEuPU4LQH2pRRz5U4HAw5LPrhaULEjgtJce/VzK4oKGy5wpd58nlvMQ4dO49KCd8xmenwsDVjQ+Tczac1rHPX7ePpOE0XhEF3uYcaarbQ5QXXSN+LDhwmn8NRZTCrhK8qPkJgwlRn9d1C0agdLuh/neJKTmHK4aZXGjI/P3hJ/61cSQ6ASd6sKcqLCAAiLjmmosJV69ExGTnWyB5iY7WVpoo3E05+Sku3nPxP1eE3Bab2FdnhjouTO5TuBtgg0fAQv+huFvs5iUglfUX6klKufIn7LLK70wB3/d/S8C2LhbSrp0KsCoy1Ap8pclpV25EhFPB0HqBuxWoIsT83Kqb864mVraCXDStuzeFBhdbI/w2sSfDHUz5SiCspFsHOgkxq9BvSvs5jURVtFuQQTrruO8Jz+OENr9p3C21SSOLAMU0gAIcAcEuCqpONMbNWWQweiGyhapT4lm89eiO1yZBdbjj3PrAWLeTy/NUUXWA2zKBy6iCOAxE4514hlTG5T+/0eP4bq4SvKJUhLSwPA8PEcfHqBsWrR89heFegMkpxYExntQ3CbdVg8Gu0yviY6Y1xDhqzUk0dTEnno0GnaHtrJlHX70Sy3ERGyk2j9qyT4o8kxnp9+Y92Cq1nN1aw+u3H503VW2l0lfEW5RGlpaRxJSmK7OZ92RQGiyiVGW4CcWBMHO4Wh6YN/ursteg53lnT2HWL8/z3O0fyhJEVYeXhiZ6b1qXV5CKUJm54QBUDGu59hto5DCCODQz/EqPNwf0kpGy1mfllaTkIgQK5ez4v2CNqXGM9/obLMOotJJXxFqQNxDz7AgCee5IYHAAFLTuk53j6kOtmfoekFpZ2+4NYdw8iwbMXhMfPS55nAOJX0mxnnznyGLjlBtr4fQhgJa72JMF9wUadJzkomOiurE3BSIMCsomLW5baDxHNeyN6qzmJSY/iKUgfsU6aQ+OenESICgNmRdtzm2n+9fJYiBjmvQgBh0sMgwwneWLCq3mJVLj/nznxKvzhCoNSD0IUR1noTiQPer/EzcW5v2ywk/aPPWSbEaIVxdbdOskr4ilJH7FOmEIiYChj5KiwUl9tWa7tSdyQhWJBtjxEbm4ERjS7ayfoNVrmsSr7aj/QFC6Mhy4lLm4fO4OVYOxuB78m64UYPpTIMEGBvDVNeqNOlWVXCV5Q69PSgn+CIvIOAPpr3j1yPJ1BzTNYjTXxkvY1JI0N4p/R2dpzsQFhoHiHC20ARK3Vp/s4sBv91ESMqnEyngqV4cbETgy1YciMv3sKB1FC0Czy/TIbwlG8y6detgQfrfh1ulfAVpQ5NT4jinwNvg8Q/sjm3P+/um0mhKxIpoUDG8Ia4lw1iFPlWPf6ekaxJ6I87W2BwRbM4Y3FDh69cgvk7s3j0iz3kVggkkIfk74FyPPZYfJVR1e3y4i3s7xx6Xk8/oAnm6/pTaYxn4cKFpKen13mMKuErSh2bnhDFC/wcgM25A/jD2qe41fMJD+heY4MYWd0uoDcQ6BKBKS8XzVzGu/Pnq6TfhD235BAuX81y2R69iXBnBwrSr4WAqXp7XryFgx0i8IpwpBT4tVi+LejOv9ofJz1pJT6fj+XLl9d5jGqWjqJcBkXuSKItJRS5q3p2ltpvj3dZrES1LcCp85GWPYjZO2bX6aLVSv3JLnVxjW4dvzfMJUkUUqDZWZvfllwxi4rTg0mw6Sns9Dl+SxEGdzQUTCffNbTq2QU8PPhPADjMJQCUldVdHfwzVMJXlMtgZdZ1TEn5ivcPziSgGcAdAOv5v27RFNJmVC6RR/LwsYO5ztwGiFapC7daNvFH+Qbmqusx8foypsXv5438MgJEYMweQoe8obU8U3KyYkn1I5svFAC73V5L20ujhnQU5TK4csAdHCvryvWp80EvMR4uQ/jPuVQnNQqJ5UHjy+xIhZgh+xli6NAg8SqX5vDmXB7WPq5O9ksDv2G79iXZ3vkMiItBi9ez3x3AL+U5z9QoYSPb3ScoSnoej3U43Uu7YjQaGTeu7u/IVj18RbkMgjdR3c1zn65kjMNA31MfYbFpzO54E4XEAAJEsL9VSBzvGe9kX2Zrbo+e16BxKz/O6jl7+Wl4sOz1uoxptN6zAlyfUWmNIrLbtVzZdhBLIn1QDN1tYBF6hK6QVfZD5O9Zi32kC80QgyPqJ+ich5nSr2d12Y66pBK+olwm0/okM01vYuWbH/HAtDvYuWc63Vqt5OeW1ykUwQVRup/0MDbdhb1So9w6hOzWezgck0unQQkNHL3yQ61+7X0iTmQR6BmD86SDqO27IBDs6UtXMZ5d72MGhnQYyKqCf3Aq1EtYn3K+8V/J/qzOPDbyCz5NvQ0ATW9kV+fepKV1vyyxqoSvKJdT2gzG3A35hVFkmeNIOV5CYddYIJjsJ291Yqqa2GF3AYfv5J38T/jboPsbLmblB8ta9TWBTaXYUnqR630FGW8hdFwxnn3z8GdtCTYKePHun0ds60Ecibqeb+yxkAkGGWB6r/l8mnRbjdlb55ZVrktqDF9RLre0GcQEyvlb+59hLxJEVPoBGJvuqk72Z5lIKU7FuTO/3sNULo5zZz7aNzaOtbHQ1WQCrAgh0NmisfS5DUPywOq20lVMgUmyPiwWkIRpGhMckneTf1Mj2UPNssp1TfXwFaUe3Gyex0uxNwEwOt3N4gEG7JW132/pEWZKPjmE52QZUdNS6zNM5Qc69fpsok6/yO6oSoZUvIxJmmrsFwYz5u7Xnu3lW6OY78+lQoTwcGmw5IaUknnSixRnn2vVCR5NObd6Wt1RPXxFqQc9Tb2ZVDyfb2J607rQz6StTiqsota2OnMZ3+iO4NyUyfolS2ptozScnC/+S2LmXwnVF/BClB27r/YFbYQ1eA+G1JvY03Mw72shNfa7DaWEFr1JK7MRAbQyG/ln59bVZZUvB9XDV5R68MyqNnRp+28eOH2AXfFh9Dp+J8Ff85okARxhxzEVdyfTIohb4eMjx/PcPP3BBohageBi5M9k5JDl8ZFsNrJ817MYdcGFxXMNevyWIozu89cplq4inDYbO3v14v0u/TGWeUEL9rEDwsv69gtpL7JZOvTyXKCtjUr4ilIPsktdtNUNZIVvL59693KndQqDPaHoNDMgAYGm8+AMPY7HWM6VO3+LvlTDE6nDUhjFgbjedB0xpqFPo8X5PLeYhw6drl6MPNPjI1wUVu8PD2jktP6GVsduqPq/DNJ0HjJ7fcPniTPY3L4bx8Pi6ZK+nkLjQSoqx7O5zSIyE/Yxq++sej0flfAVpR4kRVjJKR1Gm4gAfpfGDbYP2BA+iBBx/owMm9OFoTT4IaAvkXTeUsgJ3ZN0HbG2/gNv4Z7JyKlO9hCcWSXRIarqXQoBewui0Xd5n7iMaRjc0fgtReSnzCc9vwsfDp4YbCclmSE7MIXv4qPYjSSEJDCr76x6L6OhEr6i1IOHJ3bm0S+8UDqSHYajpFR2pVgc4Lg+FYM4m1DyUwysThrP/101kxitkDvXfMykuZtotafwe15duVzOnSI5cbuT9wOv4tBiCNUVEhPyNV/rszFmdaCk398w2IrxV0aRs3cKi2MHVT/P4i7EZN9FjCGOlbfUfVG0H0olfEWpB2eWL3xuiYnbSn/P6771/CRkIS+X/4PikGI0vYeiDlYWtRqFV1gAKNTH8cLoYNXNq+duJD09/bLcfalcWLLZSKbHR/eTHn6yazsVvvZsMUahlWzkxoNf8ZcVpZSE2Fg2oJC8nD8Q6o3EYSphY7uVlKbkAVHo/R4Mzk8xCzMPDfltg56PSviKUk+m9UmuTvwv/yLAMO19hKsD0a5UrrEbuCrZh1dYuDbvWx47/l+SPflkmeN4qfMtuIzbWPXc0xjvuU+N5dejR1MSeWPJEX6d/hUF3m4ELCbuNQSwtxmFjO2JZ988orO2MHXdcV67+knW99ODMJIiB3CEzhi8hVjL5tJed4L7hz/V4JVQVcJXlAbQbWgo+3bfTaiuEIcWR2WggkKRyLV53/Kvw89h04KzQFp78vjTsZc5NmgAVLhZ+p8XAVTSryfTE6II27eYK8Jf4EvfPJztzNzayUKeRRDvDuWX7e5mzGKwZG3h5lWwo5OVrsU9OVU6lI+2fEi/K0djn/F6Q59GNTUPX1EawJjbx7LDNYw4QxEGPOx1lhLlK+Wx4/+tTvZn2DQPXRMPcNXuYwxPP8KBv/+tgaJuebLmziLWsowXK/9IVkc9/+hhJdeqQwpBrlXH39LCWDnxVgBiymHkqWmcKh1JhjGGl9sU8WLs7gY+g5pUwleUBjLmjp6ccHXAj5lcv43h61eS7Km9pIJeV4wAbD4/qceyKHv58foNtoXK2buUr3RjCFR24r+pobj1Ne+dcOsFr/QI3nhVaLPzmbcXGcTiS43gUMJ2Pjn0SaNaxUwlfEVpIJ0GJRDXxYXZXURI0Vo6H9qBQ9S8gedw5QjezX+NV/I+Z/3gp8mN649BSvLf/qKBom5B0ueyVgzmWEgOmsFJnqX2O6PzLAK33shbXa9GAr7udkR8ZfX+2Ttm11PA/9slJXwhRJQQ4lshxJGqr5EXaHdCCLFHCLFLCLHtUo6pKM3J9N9dS5/um+mfsZkwg4f9BT3QZPAGnsOVI1hZ/kscWhwg8FiiOdztJsq6puF3nLuQhlKXsubOYtPzH1NGGEWmIpzhh4jwOWptG+MqZXbv61nVuh/SokdLMGAr/RQpgqUUchvRKmaX2sN/BFgupUwFllc9vpAxUsreUsr+l3hMRWlW+j38TzYM+TODkk6yocDHlqKh+LQYNjpuxY+lRls/Fg4lXktEqrOBom3+DqxdyeL1B1jt9tIq9jSDSzohdTCdDzBJd422JunmatPcYLIHtBQIK34Tc+UWnPZpACSENJ61DS51ls5UYHTV9+8Cq4A/XOJrKkqL45MgumrIU4L1BX7WF3TFHBGLqGUUwaHFENmz8vwdyiVJT09n+fLl5HlOYistI7m9k3adjpJZMBMEjDYsw4SbufIWCokhhkJm8CFDdev4XI5Gn7QIo9yF5ommIvIuTJ59WPQW7u/beNY2uNSEHy+lzAGQUuYIUbWMz/kksFQIIYHXpJSNZ56SojQSu3LuJsywggp/sFcvtQqEPvy8dqG6Qkwmf32H12wd3pzLio/24/dIjKQRp++ICOhpN3wRGPyYLU48nlA8nhCGWdYxjHU1nl/ojsTa7S8YvUay27yHMVCKpWQO7cUJ7h9a/+UTvs//TPhCiGVAbX+TXMw0gWFSyuyqD4RvhRAHpZRrLnC8e4B7ANq0aXMRh1CUpssSYqDi9GA69vqIfTvbITXwu9ZiDbuCgDxblMuAmyGhH5BtjuXk+hGkdHiIxISpDRh503Z4cy7L3tuPDICoql5qDoSQ1ttD7ikbOVtjQZcHiVZOHO9NaqdN6PVnV63xBIwsOnwVRCxgonkKz4zpU7Wncd4n8T/H8KWUV0gpe9TybwGQJ4RIBKj6WuucMilldtXXfGAeMLC2dlVtXpdS9pdS9o+Njf0x56QoTc6IGZ0QOpBdrTg7nUaYIeA7xInOWYToCwCNUF0+Y8JfoVXoFv7a7h7cnmwOHnycnNwFDR1+k7VxwTHkeauOwZHydE6tTMLnMGEqL8Gcc5LC7GQOHxqMyx2ClFDoiuT9/TPoviKDUQeG88ztT9X/CVykSx3S+RK4A3i26ut5P3lCiBBAJ6WsqPp+AvD0JR5XUZqVM4uWb1gxGX3fObyXcoI2WSFs696OqQk7eez4E9WlFn7X/mEWRPfhekDTXBw+9LTq5f9IjmLPeduyjIuJPhSGNzwab2wy0mhC+LyY8rNwZZXwh8xZODERZSklrKOH6/RmBvUY0gDRX7xLTfjPAnOFEHcDp4AbAIQQScAbUsqrgXhgnghefTIAH0kpv7nE4ypKs9NpUAJfrBR09EYxM7KAr/SS0OK5zIu9m3nx48821DyEFLzPb3Y9xyDrUa7otISc3AVnk376XFj+NJRlgr0VjHsS0mY0zEk1Yoc31z5d0lK+H294LJ7EtqDTAyBN5uDjHMkNlnSQkvSR0eyp7Mvazh5euH1sfYb+o11SwpdSFgHjatmeDVxd9X0G0OtSjqMoLcXVV09j3bqj9E4pZUCSm23OVbxZLHFE3Iimj0YXKMJW8hlktMKJmbWeVGyny9Ct/A9jMn5KrM9LgV5Ptl5HHySUnYaFvwm+uEr6LM5YzOwds8l15nLbzqdob8gi35+K5OzC4Ta3DmdycnWyr6bT441rFfze52OjHMbEvZv5ZkLnejyDS6OKpylKIxIsf/wQBw48QXT0fvqHBIDVLM7bQIlfh+aLIDH3Cnr7dISYt+KUJg5VJtOz4ijxPi8A8YEA4ZrGTpORPl4f+FzBHn8LT/iLMxYza8Ms3IHgXPo0djEu6kU8eiM2zU1FIJZNFbewzSCRRlOtryENJtACHPRFcO2KXTwoe/JtRdO5CU6VVlCURiYtLY0bb1xA7tYbkRL6hwT4U5KbioPP0PvIPQz3C0J1XoSAUJ2XNAqxWCpYHGKrfg2rlCQFtLMvWpbZAGfSuMzeMbs62QOMCP8vBl2AEOlGCAg3FNAj9b9YdRqi6sOzNoccoewSXXgs0AmrBoN2N5002nQiVZQW5qvCPlS6zs7DH6C56WTOBKHVaGdEI/34CB7Nf4PfFr/J4coRAMT5A5SdsAYb2VvVW9yN1bklDqy64N3Ki0NsPBE+je3+d/FnzmFC4i9JKpegnTN9Rwuw2pfCRlN3fq8Lqd4c61I9fEVRLtFGo5ni3dfi9weHF0Z4jEjd+bNKAEKlh3I9fGm18pLrXg5XjsBXqSdnq52y0+HBC7ctXG0lDhaH2FhunMgdBbcR749Gh8Cui2RcyHiSi30IrwekRHg9hGQe55gpHoN9IxM4O+RzoaJqjZFK+IrSSCVF2HCcHkbe1tvwOaPQe0IxXCC3+MzBX2W/gKWhgo2OWynYHYYM6Mg/lHxZxu/n78xi2LMraP/IYoY9u4L5O7Pq/Bh16f6+92PRB+9i7hnRDpdZx+zICG4pnIblOze3AZiEiZHm4YQe20PYwe2EH9nNyZg2GAaF0jbm7J22Lh283blmvaPGTCV8RWmkHp7YmQodVJwezLHFf8dgLSW5/U50upplFXQ6P+3abK9+7JaSjcnJlJ8Kjun7i8rrPLb5O7N49Is9ZJW6kEBWqYtHv9jTqJP+pJRJzBo6i8SQRK4JzaMo0kiuQU+sP6rW9jbDmeE0ybH2vZk/4To6et9laulUNCDHIni2u5lxY1Lq7RwulUr4itJITeuTTJvRifirevUxPT+jdau9pKZuxGx2ABKz2UFq6kZSEvZWPy9OCtoW+nn8vhdZNmAohsTEOo/tuSWHcPlqjnG7fAGeW3Kozo9VlyalTGLp9Uvpnp+F58QdxPpDKDAU19rWLUqDX0OtLB49mS4VbzGk9RW8N2wigyaGce+ESK4e15HpCbV/YDRGalqmojRit8zoxuG2UWxccIyQ2KMUuSOJiz9BXPyJGu1Wu0ZhGmKjPCyCHH8h+zPWMHr3cBaPuovIZA+pdRxXdqnrorY3Jm8s/ZCbTlSSp03ijvwE3o9bwK9ybqkxrOPXeShI+QxO6jgRayA0/+e4cmfz1LVjafwFFC5M9fAVpZHrNCiBO/42jOjF5SzbPwZPwFhj/9rACN42/5zy8EgQAp8xlmWpV7K11zpG7Pfzb3vd12NPirBe1PbGYMuWF1n4dQ/a6Z9EOkdg1OkYWz6QxHbreSP5A/IMRWhIHOZC8ru9TWX79awYfgWbuu5D+iN4eGLTucHqQlTCV5QmInS1jv45x/gw/XoKXZFICd4KA3N8t+PT17zoKHVmVqUMJaRkL5keX+0vmD4Xnu8BsyKCX9Pn/uBYHp7YGaux5p2oVqO+0SbFLVtepLT0RWxmF0JAsbyTTI/GV+VuQr96lfYZV3OywyccmXAXWaMeoiJpEwCH4/aCZuSGlHuY1ie5gc/i0qkhHUVpIgyJSYyv3Ero0QD/OnU/N+bMASEo/XmtK4viM0SzXxwnbVcWjOldc2f63GDJBV/VEMxFlmA4k/yeW3KI7FIXSRFWHp7YudEmxaKC19he0ps5p1KRsWvoFPElo4tnYpDB6ZX+yhhyt90OgL3tFgB8ATN2xyGeGvXnRlXT/lKohK8oTUTcgw+Q88STDBm8g+lxa3jz1EDcJiPhjlLKw85P+kZ/EZvj+jFz93vn7Vu89mlmx0eSa4ghwR/g/pJSJjkrL6oEw7Q+yY02wZ9re0k33j/VHWPiAnQ6H4NOT65O9mfIgJmCPddiSdiDyeTi4IHbuevAQCbd1TQKo/0QakhHUZoI+5QpJP75aQKHO3H8g0Q65RSj0zRGbP4Wo7/mVE1zQGPc0ROUEU5ckoPFq56oHr6pfK4DGzUHOUYDUghyjAZmxUQFSzM0wxIMizMWk7s0lcSIhQhdcHgr1HuBv4oqo9myeTqhu9vT/uggQqPMtbZrqlTCV5QmxD5lCqkrltP1wH7C3QEiA12YnOnhj3vdJLg0hJQkuDT+uNfDk6c6MjUkg6TBBXzszCTHlAdIbM5CHi8u5eoKR/XrunXBm5CaWwmGz1d8xPF/vcYvc3Iotp29S9lhKqm1vabzYKeCfqXpDAtby/C+zWsRJjWkoyhN1JdD4mnjHU2XaDsD8iST8pzntDBwh6cNS5F0Wl3A+8MiuI1SEgu8WKXkr4XB+edfhYUCkGvQN6sSDO4v32DTqtncvT4U28ifEOs7Rr4peM6b2yxiVMZMjNrZYR1JAHfoUa5kHUadh0jDe/iPXtlQ4V8WqoevKE3U8gEllPozCBUXruUS649ia2YHwtJjKT49iIz2Z4t+GYBZRSXVPf0EU0STLqH8eW4x/TfsI3HlLh59/x9kzPmIcO4h4C5FWKO4o+AazFUJ/mjsdlanzMFhKkYiQXMQCN/NlbYPSCN485heFBIorb12UVOleviK0kR1K+pG1rCvqDjWnXDOr+fiEh78UqNr/gD8fTpTvHMvR0v7EVvpoZNtLRAso3x/SRkrImK4f/Cj9X0KdeaDr5fzuC4MjymY0Nu7DvBp3BTWpoZi794e34l/YNOHc0/xWD7pvIUCYzHl9uPEtd5LfNcvudv2BjlrbqvxmgEZgz6ieY3hq4SvKE1UT0NPVroL2Vu6gQGRIzF+59fZLTy8Ev8JZncoFrcdjKewxw4gNusAiwy9mQzVST8xEGDW0FlNduph2cKFPOe1gmkrg/btZ/CpKxmck82jw0Ywce0X+AzBgYzKQDkiq4KnXTfRNqw7Gh6yu73Hh5W3kKTPr/GamjRTzp2ET2zXAGd0+aghHUVposaNG8egikE4PCd4Oeaj6jtF8wxFzE78kGWRm1gRsx4Ap/BwI9GMj93AlWbJYe3O6tep8FlIybJd4CiN2+HNuRx/8llKTQfpc3gnY45OYWzZXFqbdzNh02foAjVr1UtNsr1iCV4qyEz9lK+9PVhgH85PC1bg12KRUuDXYikzPoj52nsI6RNX63GbWqXQM1QPX1GaqOByiDBv3jyWxHzGkthN57VxGYI3Vun8PlYff45lhhH0iNlKmu0KMhwP0Nr2Amvz25I15z26jhhTr/FfqsObc1n54UFGuIoJK53L4JO/waiZ6OheTl66HX+P2q9t+DxeFpdamK+7i1y7g4c+eJ0pyXeSoU2G6Z3oNCiB2idtBp2pFHqmeNyZSqFAo78vQSV8RWnCziT9r7YsptJ4fuEyq9+KpklCCgyYwn+KWRfG8coKSnxHGBE1iP3fJpLfL4qKwsL6Dv2SbVxwDL9X4+sh4xHaSkK9kcTnbaH4ZAgyoMMY6sPnOH9tWmOoD52UvPT3uwAQ1igCSRK9aSUdvr4GNrQKzla6wAXs76sU2tgTvhrSUZQmLi0tjam2CehlzR6tXtPTrbA7YblgFUPR6cMRQqDTh1MWaEu208rmRBi4+iSxiU1n1aYzHMXBGTRvXpVCSqaN/QYfiSfm4asM9mNje5chDDWXgxQGjZjeFeAPzkySBj2mbtdiEBV0MPwfIM+WmbhAbaEfUym0sQwBqR6+ojQDj938F5Jefp+PzDZyDXrs3gjuyJ9G2Z5VmMKnInQ1K2wKYWSfJ8CLUy3s3dOan69t3HXsAdLT01m+fDllZWXY7XaMlt4cDdlK6tF5tHOksS88j9jeg7CEj0FYounmXo5++CJyt0XjcxgxhvqI719EueMK1lh8jAkNwdL5RkytByGp+cGAz3XBMhNJEVayaknuF6oU2piGgFTCV5Rm4ooFcOvwbAwavJz7bzzoQLcdoQ+rtb1H03HL9sfYmbyUuVf1wf+XJ+g0uCN3XHFHPUf+v6Wnp7Nw4UJ8vmBphB1FeoqFi6I2i7gtR/CmaSSvlB2mwJZKesGnVAbKSSutYEpCDpbWR3GbdRxMimJT/vUsyB7DwTA/4Vc8X/36emoZ0rpAmYmHJ3aukcDh+yuFXmgIaNfi15m26vPgcezfP4xUV9SQjqI0E4UFrSg/aCWgg1BdMIEZLMOpuMAi2xVWQZg3iiEnr8NSGYvRr+fI+gwmvf88iSt30X/DPj7PrX01qPq2fPny6mQPsMPfin1midNcQkqfIq7P3Y/mC2Nr0XIqA+V0Cc9ndHw6VuFEAFaPRueMcg6U6DhoDhCrO/taAg/hhnfPP+gFykxM65PMM9f1JDnCigCSI6w8c13PC/bWaxvquUa3jt/7XgkOH/2AYaS6ohK+ojQTltvvJXtXPPtTQ0mLnIsBNwZzV5b1suGtWboerx6WpQWHIIyaiWhHcBlEgxR0O5lLZNYDuI/M5Mll1/GnHZ/U96mcp6ysDIAjscl8MGgCRRPaIwdmoEPH5pVjuGrDV2zyH6MspSsVXfpxMGk4B3Q11/myCS+/N8zFjMbd/uBfPfoIMxFDKgmxbql5QKP1e8tMTOuTzPpHxnL82Umsf2Ts9w7N1DbU83vDXGzCW3PjmWGky0glfEVpJro8eCuGnz1MniWC28b9grmDoym16ciMNbJoQAilNh0SKLXpWDQghMzYs+P6Pi2cCZWLMOecIMRn4Xdf2hm+L4AuUMSi3X/h9a/+0XAnBtjtdo7EJrO6cx8cFhtm5wbCHO+Q5Ehi9Oa95CUmUB4fhzSZQQgqRDgLGU86NYdZkkQR4yt0jJ3eg1bPjiDxkYGETL0GprwA9taACH6d8kKdDa/UtlhMkiiqvfFlrlaqxvAVpRnp8uCt2HPDKNwfQ2FbHfvaBksDlNlgX9sIhso1zOBDBskivL4o9nS+hlMZAxkYKGaw9RjrT8UDcLprXzo5p9FzYxs8lmLWxi9iRNjKBpurP27cOF7JcuDXB1NWdPGn+PAyKHM8sSX/5euxw0FXM6n6MLKc4dW1cQCcgUhuyPyGToPOuas4bcZlGz+vbbEYt0jA5so5v/FlrlaqEr6iNDOJCVOx715DmSkcALNjPUbPPvqHt+V2wzuY8YIAs6mIAd0/JMRXSmWhH4GGTgqMpQWYSguQbEHqAkQbI/ETybtHZtN1zUsMsl3L5oL2OIo9hEaZGTK1A50G1f26ud+VlpZGReFOACZme9khixhd3p/xnj5svfk2KjQPtV2pKOPsBWstAOU79fT+xYTLGmttzlssJv3pmiuOwf8cRqoLKuErSjM0Ivs037TujF9vIKTsU/SBIu6xbkEazo4bv83drDBMROuvQ0jJvOyh9HXupNAKawZMoDw0gnBHKcM2f4vPs5LNp3owxz2VKE8pI8y7OGRN4WDABV9sp/faUOY/NOqynlOYS6PCpmfmZx8zvm9PIvR3sU+/kIKjB/C27Y9Zf/5zwmUFEqj0mSg6lID9F3/DPmXKZY3zBznz18Typ+t1lo5K+IrSDP2mX0+8G7ezNLU3ukBwvFhazi768TZ3s4yroKq0shSC9ORUomIzGL9mMakf7ScsMoRcryDcUYbP2I52bUyEDP8tYZtMZMb2ZP3ADnjMiUS4Kyg4XMTP/rqC/z4+NjjT5DIksnG7XbTJXEmPygUsCXsVcfIAJbn72RgxAmcgkWG6kxjE2fn0AQnDApu4vux37Es9wsG/vX/JMdSpyziMdCEq4StKM5SWlsZDwKYcJ5o+Gn2gCOGORFqDSX85E6uTfTUhWG0az92j3gCg9FiAnM5XsmBwd/ItdsK9ZUwFJoz5htjKo/x97w46FQ2nUC95wR7Nwj4hJKzYicXdhummR/l19Gu0K9p9UYujX1D6XJ51/wF7bDEyBo5F7ca3ZRcGTbAvvDtS04EP+hmyCBFenNLEDn8ygwr8HB7+KW1CEn/8sZsRlfAVpZlKS0vjmbhifr/lBqylb7GlMI6BiU6kwYu8wAQ9iQ6dUZI0KJ9DlhtZOmQonqrywmXmSOYGbsO0ASLdlVQY3ay1LAckYX4Ny5rBAPTVVfJTLRY9fyHDU0bxwa9458h2kiYsIb7fTF4tSiLL4yPZbOTRlESmJ0RVH79s4ULyn/83/pwcDImJxD34APa2Llj4GyJ0wfFuIeDRQ5v4b8BbFXPwg+u4FsNxb0yNs9nj6oBFf5T7+95fx+9u06QSvqI0Y9MTomDgTfxpM7xX8SnhRzrRrW0WOouGpj9/0FunaaCDqIr+LO0/pDrZn+HWW/ii/w3M2LwSqi+TCsL9BgbGn6Dbng2EOstZpNMjtAAOUxgbUgZSGtaJ1vsKSS48hkwNgDmeioJ8vlr0IVmHdnK4Qx82TLyOu+Z9xRXZ2QD4s7PJeeJJwmaUofPVvHnpQOWdWOwSKUK5p1yyxuLnoLnm3axCSvLaW5t0rf+6phK+ojRz0xOimD71PirfOc3GLnMpOGpnXNE6vh08suawjpRcsWUtDIbYw9eTN7r2vwKKzXY4Z06MQdPoVphNmLMcAKEF0Gka0V43wyPy0QylePV61sX0IssSnNHTqsRGB9d4dDHj6Fzi5MTik/wrbhIvTRvLyMIddKnYg9SF8TvPV9WHK8gdzxH9naQHbKALbrZLwZWu4D0FZ5O+pI84zr///FZdvY3NgrrxSlFaCNudzyJ9RqJSy0muKGLS2mXoAgGQEl0gwKS1yxij+xbNJzB6o4l3y1pfJ9RzgaqQhpoF2jSdDrcBNGPwZiiTpjHiaDod804zftNhpm0qw+6SVRU8QxnvjuBmw1HukltITjbhbduVnNalfGaxA/Be0T1Mtt/FKs1C4JxDGxGMdBtASkBiNB/n5c6vXOI71vyohK8oLUj33v9Ak4Lx4z8k1l3Bh088wPJf3sLHT/6aYaZVJHQ9yqnViVT6yrnvsAfLOStGWQIagzL21vrawuc9f5vfV+OxUQsw/MguBpywoDtngMFvysesK8NtDQEh8NhCiDD1Y3fhQGbou7KrwMPfl/4Fu1Z7bSC7Jnj/278woeI/DI37msSTuRfz1rQIlzSkI4S4AZgFdAUGSim3XaDdlcBsQA+8IaV89lKOqyjKj5OYMBWAw4ee5orxHxIYD4cJY+WRAbRZnUHRofHoPEWkW1czXn8VAC93MpNnEcS7NX5/7AtCC/exQ/Tiu8M6UtMwF5xf410azl+AxOz3oxMh5213hp5A6mp+wAQMBsL0KTgjXKwZu5o4g44YTzEeS/T5r+spJqayjPtWl1Pid0CXy3vXalN0qWP4e4HrgNcu1EAIoQdeBsYDmcBWIcSXUsr9l3hsRVF+hMSEqdWJ/4xrx8KBbitZ9eFrVLoc5HmyOO0uY1SWgStzfOhEAXb9u2hyE2vz2xIWH0mFsTUSHQ6zldPWEPoe21PjNaUQeOLOLyqm83nRdB70mqXGdk3vqTVel9VKt9JunGpzirljNR468gmBkp/g5+zzdQEPHTK+BMDklyRvs8B9l/eu1abokhK+lPIAgDh3Pm9NA4GjUsqMqrZzgKmASviK0oh0HTHmvFo5hzfnsmLBMRzFEZgCt9P+dDj5cbGIkycJ9eXjMWoUjRvH7lY9yLeGMmbTEkIrK7B4fUR7BUc62mu8ngSoKMJpPUKYsxuCszOFdAETmuH8YSGry4W0BRdZ9+nhnQ77eOnwK2x03IpDi8HqK6b9kYUk5J8dYPBX6uv9pqamoD5m6SQDp7/zOBMYdKHGQoh7gHsA2rRpc3kjUxTle3UalFCjTk5OrhHrsX/y1dbhfOm0ocUtpUP2p9y8ahkhbj0xjnJ6ZTuxuFzorYJ27RxsjBlIGWGYpY82WjvckacpyNtKRbgOHF0IkzrKhcRRbCYsqpKA4Wxa0vv9WJ1OykPOXhDONejpZFtLJ9taALxOPcfy42vEbUhMuszvTNP0PxO+EGIZUFtlpMellAt+wDFq6/7XfvkfkFK+DrwO0L9//wu2UxSl/p0ZDho2DP4K/PMlF/+tGEZ6IvTlIPtpT7tONgaaStCbjzGqaCU/d7/HyNEfkGlJYGK2lx6laWj2LzAe38weu5f1pBJAD3RhUsFWWtldeKwWrC4XVqeTwthoToZkVMeQ4K85R8doO2f+vcVC3IMPXP43own6nwlfSnnFJR4jE2j9ncetgOxLfE1FURqBnu2X8WSemxd9Y9gpuzCyaC27YtJ4j3AiZAdOxplYJYczfPsW5g2YyJIkM0uSAG7G0t2Nx2TGfiQP/Qk3Xs3A2vD+9JfFtCEDl9WGy2LF5TvC7tjg9QGLpnF/SWmNGFzSSHmolTCHC2NSUvDu3MZQIK0Rqo8hna1AqhCiPZAFzARurofjKopymcXZf0VSlydYf+xN/pXzKfqKI6RV7CWiQxlJ/fMxhvrxOYzY9k+g+wGNf3Qvo0IfjnAHIGsnN1bs5q6i6URpUcw3HWIvRdy6dAHRZaVU2mys7JfMNwOLQIJZhPB4YSaTnJXVx/ehY4OhHfeNfpw/dTVw890q0X+fS52WeS3wIhALLBZC7JJSThRCJBGcfnm1lNIvhPgVsITgtMy3pJT7LjlyRVEaXJ/ht7MT2ON9nATnNxS6xyArl1B6zE7pMTtWfTi9IkfSNqw7Hcr8dEp9GL+1CCyQ7jTwQbgJrVQjypdGbGEnesoObB2UjCv0GPuTk9mc0gOH2cJIVnCr/wNiiyyU+72E6T2U+y2sK+/Ao6YH+VM3lex/CCFl4x0m79+/v9y2rdap/YqiNCKv33cXFYUF5IWNIlqzYKjcALKCA+1+zS+EhTgE+UgOJ80jous3mPXBG7IWLr+HzW0W4zCX0MvtJs9gIM+gZ2pxPxJKhzF7QDfKQ0KCtY71ghC3i0HH95GUV8BxU3tumzTye9eTbYmEENullP1r26dq6SiKcslGzLydpa+/RHzF6uptrcpdfOIp4nrL2amZ7XP7kKLZmZC6mGhLCV0qO5C6cxZHorexusMcJlSW8NB2F6W7N+Cv3MyERQEi0ip5M+5OHvnHX6teZWg9n13zoRK+oiiX7Mz8/bVz3qOiqJCw6BjSfnU7j4V24tEv9uDynZ1JMzC/P0/kDsCL4P6CFRhDJpBaFOyQrmmzCPqd5v6UEhICPnK0GF7y3MHXttE80iBn1ryohK8oSp2o7catrlVfzyzg3c+YRY92q/nDoRm8jkaplkWEcykG6wg6FvajVVFPlllhqPnsylVmg+Dv13SrxzNpvtQYvqIo9eZPs2YRF5tBvzBJfMZ1ZBXksa3oGwLSX93mSGhn1sYOwilDiLOZeOyabmqc/iKoMXxFURoFp8lMQUEK28mg3cA/YTY7abdpINn7JS6/A4shlKiEXCZoR7j32rtr3OWrXDqV8BVFqTcVXZIx7z1BQUEKBQUpAOiljl7tW7Esdi3puu2MOjSEzuGjVbK/DFTCVxSl3rx23e38nPcIPZRFqMeD02ShzGLFdspK58Lb6MxtGEw6hkzt0NChNksq4SuKUq9eu+72Go8Pb85lY+ExHG4PoVFmhkztoHr3l4lK+IqiNKhzK3Iql49a4lBRFKWFUAlfURSlhVAJX1EUpYVQCV9RFKWFUAlfURSlhWjUpRWEEAXAyR/59BigsA7DqW9NPX5Q59AYNPX4oemfQ33H31ZKGVvbjkad8C+FEGLbhepJNAVNPX5Q59AYNPX4oemfQ2OKXw3pKIqitBAq4SuKorQQzTnhv97QAVyiph4/qHNoDJp6/ND0z6HRxN9sx/AVRVGUmppzD19RFEX5DpXwFUVRWohml/CFEFcKIQ4JIY4KIZrcusdCiLeEEPlCiL0NHcuPJYRoLYRYKYQ4IITYJ4S4v6FjuhhCCIsQYosQYndV/E81dEw/hhBCL4TYKYRY1NCx/BhCiBNCiD1CiF1CiCa51qkQIkII8ZkQ4mDV78OQBo2nOY3hCyH0wGFgPJAJbAVuklLub9DALoIQYiTgAN6TUvZo6Hh+DCFEIpAopdwhhAgDtgPTmsr/gxBCACFSSocQwgisA+6XUm5q4NAuihDit0B/IFxKObmh47lYQogTQH8pZZO96UoI8S6wVkr5hhDCBNiklKUNFU9z6+EPBI5KKTOklF5gDjC1gWO6KFLKNUBxQ8dxKaSUOVLKHVXfVwAHgCazCrUMclQ9NFb9a1I9IyFEK2AS8EZDx9JSCSHCgZHAmwBSSm9DJntofgk/GTj9nceZNKFE0xwJIdoBfYDNDRzKRakaDtkF5APfSimbVPzAv4HfA1oDx3EpJLBUCLFdCHFPQwfzI6QABcDbVUNrbwghQhoyoOaW8EUt25pUz6w5EUKEAp8DD0gpyxs6noshpQxIKXsDrYCBQogmM7wmhJgM5Esptzd0LJdomJSyL3AVcF/VcGdTYgD6Aq9KKfsATqBBrys2t4SfCbT+zuNWQHYDxdKiVY19fw58KKX8oqHj+bGq/gRfBVzZsJFclGHANVVj4HOAsUKIDxo2pIsnpcyu+poPzCM4ZNuUZAKZ3/nr8DOCHwANprkl/K1AqhCifdUFkpnAlw0cU4tTddHzTeCAlPL/GjqeiyWEiBVCRFR9bwWuAA42aFAXQUr5qJSylZSyHcHfgRVSylsbOKyLIoQIqbrgT9UwyASgSc1ck1LmAqeFEJ2rNo0DGnTiQrNaxFxK6RdC/ApYAuiBt6SU+xo4rIsihPgYGA3ECCEygT9JKd9s2Kgu2jDgNmBP1Tg4wGNSyq8aLqSLkgi8WzXrSwfMlVI2yamNTVg8MC/Yd8AAfCSl/KZhQ/pRfg18WNUBzQDuashgmtW0TEVRFOXCmtuQjqIoinIBKuEriqK0ECrhK4qitBAq4SuKorQQKuEriqK0ECrhK4qitBAq4SuKorQQ/w8BgtXyzwmmcgAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] @@ -1579,7 +1579,7 @@ " for i, (x_i, y_i) in enumerate(sine_loader):\n", "\n", " y_hat_i = model(x_i) # forward pass\n", - " \n", + "\n", " loss = criterion(y_hat_i, y_i) # compute the loss and perform the backward pass\n", "\n", " optimizer.zero_grad() # cleans the gradients\n", @@ -1599,7 +1599,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.0022552500595338643\n" + "0.005281522491713986\n" ] } ], @@ -1632,7 +1632,7 @@ "def enforce_reproducibility(seed=42):\n", " # Sets seed manually for both CPU and CUDA\n", " torch.manual_seed(seed)\n", - " # For atomic operations there is currently \n", + " # For atomic operations there is currently\n", " # no simple way to enforce determinism, as\n", " # the order of parallel operations is not known.\n", " #\n", @@ -1645,6 +1645,13 @@ "enforce_reproducibility()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The function `utils.fix_random_seeds()` extends the above to the random seeds for NumPy and the Python `random` library." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1678,9 +1685,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/tutorial_pytorch_models.ipynb b/tutorial_pytorch_models.ipynb index 2583871..4f7e587 100644 --- a/tutorial_pytorch_models.ipynb +++ b/tutorial_pytorch_models.ipynb @@ -14,7 +14,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -53,10 +53,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "torch_autoencoder.py torch_rnn_classifier.py\r\n", - "torch_color_describer.py torch_shallow_neural_classifier.py\r\n", - "torch_glove.py torch_tree_nn.py\r\n", - "torch_model_base.py\r\n" + "torch_autoencoder.py torch_rnn_classifier.py\n", + "torch_color_describer.py torch_shallow_neural_classifier.py\n", + "torch_glove.py torch_tree_nn.py\n", + "torch_model_base.py\n" ] } ], @@ -107,6 +107,7 @@ "from sklearn.model_selection import GridSearchCV\n", "import torch\n", "import torch.nn as nn\n", + "\n", "from torch_model_base import TorchModelBase\n", "from torch_shallow_neural_classifier import TorchShallowNeuralClassifier\n", "from torch_rnn_classifier import TorchRNNDataset, TorchRNNClassifier, TorchRNNModel\n", @@ -303,7 +304,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 0.4739058315753937" + "Finished epoch 1000 of 1000; error is 0.5476832389831543" ] } ], @@ -332,12 +333,12 @@ " precision recall f1-score support\n", "\n", " 0 1.00 1.00 1.00 19\n", - " 1 0.92 0.73 0.81 15\n", - " 2 0.79 0.94 0.86 16\n", + " 1 1.00 0.60 0.75 15\n", + " 2 0.73 1.00 0.84 16\n", "\n", - " accuracy 0.90 50\n", - " macro avg 0.90 0.89 0.89 50\n", - "weighted avg 0.91 0.90 0.90 50\n", + " accuracy 0.88 50\n", + " macro avg 0.91 0.87 0.86 50\n", + "weighted avg 0.91 0.88 0.87 50\n", "\n" ] } @@ -362,15 +363,15 @@ "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 0.58722406625747686" + "Finished epoch 1000 of 1000; error is 0.4063138961791992" ] }, { "data": { "text/plain": [ - "{'fit_time': array([1.90538383, 1.82407284, 1.84190989, 1.83592701, 1.84237123]),\n", - " 'score_time': array([0.00169611, 0.0011301 , 0.00174618, 0.00141382, 0.0018909 ]),\n", - " 'test_score': array([0.68660969, 0.84242424, 0.84615385, 0.51515152, 0.76911977])}" + "{'fit_time': array([1.55139804, 1.55899596, 1.52245688, 1.54286432, 1.59223175]),\n", + " 'score_time': array([0.00128269, 0.00121689, 0.00102687, 0.00095797, 0.0013411 ]),\n", + " 'test_score': array([0.93732194, 0.84242424, 0.84615385, 0.64444444, 0.95681511])}" ] }, "execution_count": 12, @@ -398,7 +399,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -423,7 +424,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -447,7 +448,7 @@ "\thidden_dim2=50)" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -460,14 +461,14 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 0.023747699335217476" + "Finished epoch 1000 of 1000; error is 0.022516299039125443" ] } ], @@ -477,7 +478,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -486,7 +487,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -519,14 +520,14 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 0.060364335775375366" + "Finished epoch 1000 of 1000; error is 0.118631362915039066" ] } ], @@ -542,16 +543,16 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.9672889488678962" + "0.9656695156695158" ] }, - "execution_count": 19, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -562,13 +563,14 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "GridSearchCV(estimator=TorchDeeperNeuralClassifier(\n", + "GridSearchCV(cv=None, error_score=nan,\n", + " estimator=TorchDeeperNeuralClassifier(\n", "\tbatch_size=1028,\n", "\tmax_iter=1000,\n", "\teta=0.001,\n", @@ -584,10 +586,13 @@ "\thidden_activation=Tanh(),\n", "\thidden_dim1=50,\n", "\thidden_dim2=50),\n", - " param_grid={'hidden_dim1': [5, 10], 'hidden_dim2': [5, 10]})" + " iid='deprecated', n_jobs=None,\n", + " param_grid={'hidden_dim1': [5, 10], 'hidden_dim2': [5, 10]},\n", + " pre_dispatch='2*n_jobs', refit=True, return_train_score=False,\n", + " scoring=None, verbose=0)" ] }, - "execution_count": 20, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -619,7 +624,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ @@ -634,7 +639,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -657,7 +662,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -686,7 +691,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 25, "metadata": {}, "outputs": [], "source": [ @@ -732,7 +737,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -753,7 +758,7 @@ "\ttol=1e-05)" ] }, - "execution_count": 25, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -766,7 +771,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 27, "metadata": {}, "outputs": [ { @@ -783,7 +788,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -792,16 +797,16 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.3236728529459678" + "0.32367282328989977" ] }, - "execution_count": 28, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -826,7 +831,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -861,7 +866,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 31, "metadata": {}, "outputs": [ { @@ -884,7 +889,7 @@ "\thidden_activation=Tanh())" ] }, - "execution_count": 30, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -897,14 +902,14 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 132.6202392578125" + "Finished epoch 1000 of 1000; error is 129.07626342773438" ] } ], @@ -914,7 +919,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -923,16 +928,16 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "-0.3762662051157306" + "-0.3409709560634049" ] }, - "execution_count": 33, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } @@ -964,7 +969,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -980,7 +985,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -996,7 +1001,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -1005,7 +1010,7 @@ "['La', 'compañía', 'estatal', 'de', 'electricidad', 'de', 'Suecia', ',']" ] }, - "execution_count": 36, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } @@ -1023,7 +1028,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 38, "metadata": {}, "outputs": [ { @@ -1032,7 +1037,7 @@ "['O', 'O', 'O', 'O', 'O', 'O', 'B-LOC', 'O']" ] }, - "execution_count": 37, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -1050,7 +1055,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 39, "metadata": {}, "outputs": [], "source": [ @@ -1088,7 +1093,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 40, "metadata": {}, "outputs": [], "source": [ @@ -1099,7 +1104,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -1110,7 +1115,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 42, "metadata": {}, "outputs": [], "source": [ @@ -1128,22 +1133,22 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "tensor([[[ 0.3255, 0.2848, 0.3470, -0.1150],\n", - " [ 0.2264, 0.3246, 0.3123, -0.1394],\n", - " [ 0.1972, 0.3036, 0.3240, -0.0696]],\n", + "tensor([[[-0.1742, -0.3690, -0.1535, 0.5515],\n", + " [-0.1789, -0.5332, -0.2079, 0.5774],\n", + " [-0.1241, -0.5240, -0.1012, 0.4975]],\n", "\n", - " [[ 0.3255, 0.2848, 0.3470, -0.1150],\n", - " [ 0.2272, 0.2959, 0.3383, -0.0673],\n", - " [ 0.1895, 0.3257, 0.3078, -0.1153]]], grad_fn=)" + " [[-0.1742, -0.3690, -0.1535, 0.5515],\n", + " [-0.1159, -0.4871, -0.0897, 0.4917],\n", + " [-0.1467, -0.5842, -0.1833, 0.5616]]], grad_fn=)" ] }, - "execution_count": 42, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } @@ -1167,7 +1172,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 44, "metadata": {}, "outputs": [], "source": [ @@ -1229,7 +1234,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 45, "metadata": {}, "outputs": [], "source": [ @@ -1241,22 +1246,22 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 17. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 8.602030873298645" + "Stopping after epoch 16. Validation score did not improve by tol=1e-05 for more than 10 epochs. Final error is 9.231323719024658" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 24min 41s, sys: 3min 21s, total: 28min 3s\n", - "Wall time: 10min 22s\n" + "CPU times: user 22min 44s, sys: 1min 37s, total: 24min 21s\n", + "Wall time: 8min 5s\n" ] } ], @@ -1266,16 +1271,16 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 47, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.11311924082554141" + "0.10711347174938976" ] }, - "execution_count": 46, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" } @@ -1301,9 +1306,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.7.6" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/utils.py b/utils.py index f365ec6..b6a463a 100644 --- a/utils.py +++ b/utils.py @@ -12,7 +12,7 @@ import os __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" START_SYMBOL = "" @@ -177,8 +177,11 @@ def fit_classifier_with_hyperparameter_search( basemod : an sklearn model class instance This is the basic model-type we'll be optimizing. - cv : int - Number of cross-validation folds. + cv : int or an sklearn Splitter + Number of cross-validation folds, or the object used to define + the splits. For example, where there is a predefeined train/dev + split one wants to use, one can feed in a `PredefinedSplitter` + instance to use that split during cross-validation. param_grid : dict A dict whose keys name appropriate parameters for `basemod` and @@ -203,9 +206,10 @@ def fit_classifier_with_hyperparameter_search( A trained model instance, the best model found. """ - splitter = StratifiedShuffleSplit(n_splits=cv, test_size=0.20) + if isinstance(cv, int): + cv = StratifiedShuffleSplit(n_splits=cv, test_size=0.20) # Find the best model within param_grid: - crossvalidator = GridSearchCV(basemod, param_grid, cv=splitter, scoring=scoring) + crossvalidator = GridSearchCV(basemod, param_grid, cv=cv, scoring=scoring) crossvalidator.fit(X, y) # Report some information: if verbose: diff --git a/vsm.py b/vsm.py index e224ac4..45e663d 100644 --- a/vsm.py +++ b/vsm.py @@ -1,4 +1,3 @@ -import codecs from collections import defaultdict import matplotlib.pyplot as plt import numpy as np @@ -8,10 +7,12 @@ from sklearn.manifold import TSNE import scipy import scipy.spatial.distance +from scipy.stats import spearmanr +import torch import utils __author__ = "Christopher Potts" -__version__ = "CS224u, Stanford, Fall 2020" +__version__ = "CS224u, Stanford, Spring 2021" def euclidean(u, v): @@ -267,3 +268,249 @@ def lsa(df, k=100): singvals = np.diag(singvals) trunc = np.dot(rowmat[:, 0:k], singvals[0:k, 0:k]) return pd.DataFrame(trunc, index=df.index) + + +def hf_represent(batch_ids, model, layer=-1): + """ + Encode a batch of sequences of ids using a Hugging Face + Transformer-based model `model`. The model's `forward` method is + `output_hidden_states=True`, and we get the hidden states from + `layer`. + + + Parameters + ---------- + batch_ids : iterable, shape (n_examples, n_tokens) + Sequences of indices into the model vocabulary. + + model : Hugging Face transformer model + + later : int + The layer to return. This will get all the hidden states at + this layer. `layer=0` gives the embedding, and `layer=-1` + gives the final output states. + + Returns + ------- + Tensor of shape `(n_examples, n_tokens, n_dimensions)` + where `n_dimensions` is the dimensionality of the + Transformer model + + """ + with torch.no_grad(): + reps = model(batch_ids, output_hidden_states=True) + return reps.hidden_states[layer] + + +def hf_encode(text, tokenizer, add_special_tokens=False): + """ + Get the indices for the tokens in `text` according to `tokenizer`. + If no tokens can be obtained from `text`, then the tokenizer.unk_token` + is used as the only token. + + Parameters + ---------- + text: str + + tokenizer: Hugging Face tokenizer + + add_special_tokens : bool + A Hugging Face parameter to the tokenizer. + + Returns + ------- + torch.Tensor of shape `(1, m)` + A batch of 1 example of `m` tokens`, where `m` is determined + by `text` and the nature of `tokenizer`. + + """ + encoding = tokenizer.encode( + text, + add_special_tokens=add_special_tokens, + return_tensors='pt') + if encoding.shape[1] == 0: + text = tokenizer.unk_token + encoding = torch.tensor([[tokenizer.vocab[text]]]) + return encoding + + +def mean_pooling(hidden_states): + """ + Get the mean along `axis=1` of a Tensor. + + Parameters + ---------- + hidden_states : torch.Tensor, shape `(k, m, n)` + Where `k` is the number of examples, `m` is the number of vectors + for each example, and `n` is dimensionality of each vector. + + Returns + ------- + torch.Tensor of dimension `(k, n)`. + + """ + _check_pooling_dimensionality(hidden_states) + return torch.mean(hidden_states, axis=1) + + +def max_pooling(hidden_states): + """ + Get the max values along `axis=1` of a Tensor. + + Parameters + ---------- + hidden_states : torch.Tensor, shape `(k, m, n)` + Where `k` is the number of examples, `m` is the number of vectors + for each example, and `n` is dimensionality of each vector. + + Raises + ------ + ValueError + If `hidden_states` does not have 3 dimensions. + + Returns + ------- + torch.Tensor of dimension `(k, n)`. + + """ + _check_pooling_dimensionality(hidden_states) + return torch.amax(hidden_states, axis=1) + + +def min_pooling(hidden_states): + """ + Get the min values along `axis=1` of a Tensor. + + Parameters + ---------- + hidden_states : torch.Tensor, shape `(k, m, n)` + Where `k` is the number of examples, `m` is the number of vectors + for each example, and `n` is dimensionality of each vector. + + Raises + ------ + ValueError + If `hidden_states` does not have 3 dimensions. + + Returns + ------- + torch.Tensor of dimension `(k, n)`. + + """ + _check_pooling_dimensionality(hidden_states) + return torch.amin(hidden_states, axis=1) + + +def last_pooling(hidden_states): + """Get the final vector in second dimension (`axis=1`) of a Tensor. + + Parameters + ---------- + hidden_states : torch.Tensor, shape (b, m, n) + Where b is the number of examples, m is the number of vectors + for each example, and `n` is dimensionality of each vector. + + Raises + ------ + ValueError + If `hidden_states` does not have 3 dimensions. + + Returns + ------- + torch.Tensor of dimension `(k, n)`. + + """ + _check_pooling_dimensionality(hidden_states) + return hidden_states[:, -1] + + +def _check_pooling_dimensionality(hidden_states): + if not len(hidden_states.shape) == 3: + raise ValueError( + "The input to the pooling function should have 3 dimensions: " + "it's a batch of k examples, where each example has m vectors, " + "each of dimensionality n. The function will pool the vectors " + "for each example, returning a Tensor of shape (k, n).") + + +def create_subword_pooling_vsm(vocab, tokenizer, model, layer=1, pool_func=mean_pooling): + vocab_ids = [hf_encode(w, tokenizer) for w in vocab] + vocab_hiddens = [hf_represent(w, model, layer=layer) for w in vocab_ids] + pooled = [pool_func(h) for h in vocab_hiddens] + pooled = [p.squeeze().cpu().numpy() for p in pooled] + return pd.DataFrame(pooled, index=vocab) + + +def word_relatedness_evaluation(dataset_df, vsm_df, distfunc=cosine): + """ + Main function for word relatedness evaluations used in the assignment + and bakeoff. The function makes predictions for word pairs in + `dataset_df` using `vsm_df` and `distfunc`, and it returns a copy of + `dataset_df` with a new column `'prediction'`, as well as the Spearman + rank correlation between those preductions and the `'score'` column + in `dataset_df`. + + The prediction for a word pair (w1, w1) is determined by applying + `distfunc` to the representations of w1 and w2 in `vsm_df`. We return + the negative of this value since it is assumed that `distfunc` is a + distance function and the scores in `dataset_df` are for positive + relatedness. + + Parameters + ---------- + dataset_df : pd.DataFrame + Required to have columns {'word1', 'word2', 'score'}. + + vsm_df : pd.DataFrame + The vector space model used to get representations for the + words in `dataset_df`. The index must contain every word + represented in `dataset_df`. + + distfunc : function mapping vector pairs to floats (default: `cosine`) + The measure of distance between vectors. Can also be `euclidean`, + `matching`, `jaccard`, as well as any other distance measure + between 1d vectors. + + Raises + ------ + ValueError + If any words in `dataset_df` are not in the index of `vsm_df`. + + Returns + ------- + tuple (dataset_df, rho) + Where `dataset_df` is a `pd.DataFrame` -- a copy of the + input with a new column `'prediction'` -- and `rho` is a float + giving the Spearman rank correlation between the `'score'` + and `prediction` values. + + """ + dataset_df = dataset_df.copy() + + dataset_vocab = set(dataset_df.word1.values) | set(dataset_df.word2.values) + + vsm_vocab = set(vsm_df.index) + + missing = dataset_vocab - vsm_vocab + + if missing: + raise ValueError( + "The following words are in the evaluation dataset but not in the " + "VSM. Please switch to a VSM with an appropriate vocabulary:\n" + "{}".format(sorted(missing))) + + def predict(row): + x1 = vsm_df.loc[row.word1] + x2 = vsm_df.loc[row.word2] + return -distfunc(x1, x2) + + dataset_df['prediction'] = dataset_df.apply(predict, axis=1) + + rho = None + + if 'score' in dataset_df.columns: + rho, pvalue = spearmanr( + dataset_df.score.values, + dataset_df.prediction.values) + + return dataset_df, rho diff --git a/vsm_01_distributional.ipynb b/vsm_01_distributional.ipynb index c162dce..7375852 100644 --- a/vsm_01_distributional.ipynb +++ b/vsm_01_distributional.ipynb @@ -18,7 +18,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -32,8 +32,8 @@ "## Contents\n", "\n", "1. [Overview](#Overview)\n", - "1. [Motivation](#Motivation)\n", - "1. [Terminological notes](#Terminological-notes)\n", + " 1. [Motivation](#Motivation)\n", + " 1. [Terminological notes](#Terminological-notes)\n", "1. [Set-up](#Set-up)\n", "1. [Matrix designs](#Matrix-designs)\n", "1. [Pre-computed example matrices](#Pre-computed-example-matrices)\n", @@ -41,6 +41,7 @@ " 1. [Euclidean](#Euclidean)\n", " 1. [Length normalization](#Length-normalization)\n", " 1. [Cosine distance](#Cosine-distance)\n", + " 1. [Cosine distance that's really a distance metric](#Cosine-distance-that's-really-a-distance-metric)\n", " 1. [Matching-based methods](#Matching-based-methods)\n", " 1. [Summary](#Summary)\n", "1. [Distributional neighbors](#Distributional-neighbors)\n", @@ -56,7 +57,6 @@ { "cell_type": "markdown", "metadata": { - "collapsed": true, "slideshow": { "slide_type": "slide" } @@ -77,7 +77,7 @@ } }, "source": [ - "## Motivation\n", + "### Motivation\n", "\n", "Why build distributed representations? There are potentially many reasons. The two we will emphasize in this course:\n", "\n", @@ -94,14 +94,12 @@ } }, "source": [ - "## Terminological notes" + "### Terminological notes" ] }, { "cell_type": "markdown", - "metadata": { - "collapsed": true - }, + "metadata": {}, "source": [ "* The distributed representations we build will always be vectors of real numbers. The models are often called __vector space models__ (VSMs).\n", "\n", @@ -137,10 +135,10 @@ "metadata": {}, "outputs": [], "source": [ - "%matplotlib inline\n", "import numpy as np\n", "import os\n", "import pandas as pd\n", + "\n", "import vsm\n", "import utils" ] @@ -206,12 +204,12 @@ "\n", "* The vocabulary is the top 5K most frequent unigrams.\n", "\n", - "Two come from IMDB user-supplied movie reviews, and two come from Gigaword, a collection of newswire and newspaper text. Further details:\n", + "Two come from Yelp user-supplied reviews of products and services, and two come from Gigaword, a collection of newswire and newspaper texts. Further details:\n", "\n", "|filename | source | window size| count weighting |\n", "|---------|--------|------------|-----------------|\n", - "|imdb_window5-scaled.csv.gz | IMDB movie reviews | 5| 1/d |\n", - "|imdb_window20-flat.csv.gz | IMDB movie reviews | 20| 1 |\n", + "|yelp_window5-scaled.csv.gz | Yelp reviews | 5| 1/d |\n", + "|yelp_window20-flat.csv.gz | Yelp reviews | 20| 1 |\n", "|gigaword_window5-scaled.csv.gz | Gigaword | 5 | 1/d |\n", "|gigaword_window20-flat.csv.gz | Gigaword | 20 | 1 |\n", "\n", @@ -224,8 +222,8 @@ "metadata": {}, "outputs": [], "source": [ - "imdb5 = pd.read_csv(\n", - " os.path.join(DATA_HOME, 'imdb_window5-scaled.csv.gz'), index_col=0)" + "yelp5 = pd.read_csv(\n", + " os.path.join(DATA_HOME, 'yelp_window5-scaled.csv.gz'), index_col=0)" ] }, { @@ -234,8 +232,8 @@ "metadata": {}, "outputs": [], "source": [ - "imdb20 = pd.read_csv(\n", - " os.path.join(DATA_HOME, 'imdb_window20-flat.csv.gz'), index_col=0)" + "yelp20 = pd.read_csv(\n", + " os.path.join(DATA_HOME, 'yelp_window20-flat.csv.gz'), index_col=0)" ] }, { @@ -258,6 +256,33 @@ " os.path.join(DATA_HOME, 'giga_window20-flat.csv.gz'), index_col=0)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "These count matrices all have the same vocabulary/index, which you can extract from their indices:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['):', ');', '..', '...', ':(', ':)', ':/', ':D', ':|', ';p', '___', 'abandon']" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(yelp5.index[: 12])" + ] + }, { "cell_type": "markdown", "metadata": { @@ -308,21 +333,21 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "ABC = pd.DataFrame([\n", - " [ 2.0, 4.0], \n", - " [10.0, 15.0], \n", + " [ 2.0, 4.0],\n", + " [10.0, 15.0],\n", " [14.0, 10.0]],\n", " index=['A', 'B', 'C'],\n", - " columns=['x', 'y']) " + " columns=['x', 'y'])" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -352,17 +377,17 @@ " \n", " \n", " \n", - " A\n", + " A\n", " 2.0\n", " 4.0\n", " \n", " \n", - " B\n", + " B\n", " 10.0\n", " 15.0\n", " \n", " \n", - " C\n", + " C\n", " 14.0\n", " 10.0\n", " \n", @@ -377,7 +402,7 @@ "C 14.0 10.0" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -388,7 +413,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -403,12 +428,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -432,7 +457,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -445,7 +470,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -500,7 +525,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -509,12 +534,12 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", "text/plain": [ "
" ] @@ -526,12 +551,12 @@ } ], "source": [ - "plot_ABC(ABC_normed) " + "plot_ABC(ABC_normed)" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -574,7 +599,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -597,6 +622,97 @@ "So, in building in the length normalization, cosine distance achieves our goal of associating A and B and separating both from C." ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Cosine distance that's really a distance metric" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To qualify as a distance metric, a vector comparison method $d$ must:\n", + "\n", + "1. be symmetric: $d(x, y) = d(y, x)$\n", + "1. assign 0 to identical vectors: $d(x, x) = 0$, and \n", + "1. satisfy the triangle inequality: $d(x, z) \\leq d(x, y) + d(y, z)$\n", + "\n", + "Cosine distance as defined above does not satisfy the triangle inequality. For example:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "c1 = np.array([0.02383781, 0.03891728])\n", + "c2 = np.array([0.10797527, 0.15304325])\n", + "c3 = np.array([0.22342269, 0.02145921])\n", + "\n", + "vsm.cosine(c1, c3) <= vsm.cosine(c1, c2) + vsm.cosine(c2, c3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To correct this, one can use `proper_cosine`:" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "def proper_cosine(u, v):\n", + " num = (u * v).sum()\n", + " den = vsm.vector_length(u) * vsm.vector_length(v)\n", + " sim = num / den\n", + " return np.arccos(sim) / np.pi" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "proper_cosine(c1, c3) <= proper_cosine(c1, c2) + proper_cosine(c2, c3)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This will generally yield values that are roughly proportional to the ones we obtain with `vsm.cosine`, so the extra effort is probably not worth it!" + ] + }, { "cell_type": "markdown", "metadata": { @@ -634,7 +750,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -650,8 +766,8 @@ "source": [ "for m in (vsm.euclidean, vsm.cosine, vsm.jaccard):\n", " fmt = {\n", - " 'n': m.__name__, \n", - " 'AB': m(ABC.loc['A'], ABC.loc['B']), \n", + " 'n': m.__name__,\n", + " 'AB': m(ABC.loc['A'], ABC.loc['B']),\n", " 'BC': m(ABC.loc['B'], ABC.loc['C'])}\n", " print('{n:>15}(A, B) = {AB:5.2f} {n:>15}(B, C) = {BC:5.2f}'.format(**fmt))" ] @@ -673,7 +789,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -685,7 +801,7 @@ "dtype: float64" ] }, - "execution_count": 20, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -696,7 +812,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -708,7 +824,7 @@ "dtype: float64" ] }, - "execution_count": 21, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -719,127 +835,152 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000e+00\n", - "job 1.191396e+06\n", - "pretty 1.192212e+06\n", - "e 1.194603e+06\n", - "guys 1.194643e+06\n", + "superb 0.000000\n", + "terrific 4515.215320\n", + "disgusting 5569.114329\n", + "somewhat 5690.118149\n", + "phenomenal 5790.836484\n", "dtype: float64" ] }, - "execution_count": 22, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb5, distfunc=vsm.euclidean).head()" + "vsm.neighbors('superb', yelp5, distfunc=vsm.euclidean).head()" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000e+00\n", - "really 1.709370e+06\n", - "great 1.746426e+06\n", - "well 1.757869e+06\n", - "story 1.760839e+06\n", + "superb 0.000000\n", + "presented 23766.148657\n", + "beautifully 24212.032587\n", + "bomb 26589.742609\n", + "gorgeous 26607.813570\n", "dtype: float64" ] }, - "execution_count": 23, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb20, distfunc=vsm.euclidean).head()" + "vsm.neighbors('superb', yelp20, distfunc=vsm.euclidean).head()" ] }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000\n", - "measure 0.819398\n", - ". 0.843800\n", - "luck 0.863481\n", - "pretty 0.868561\n", + "superb 0.000000\n", + "phenomenal 0.012159\n", + "outstanding 0.012170\n", + "fantastic 0.015080\n", + "terrific 0.016488\n", "dtype: float64" ] }, - "execution_count": 24, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb5, distfunc=vsm.cosine).head()" + "vsm.neighbors('superb', yelp5, distfunc=vsm.cosine).head()" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000\n", - ". 0.133102\n", - "pretty 0.183657\n", - "acting 0.185801\n", - "measure 0.192544\n", + "superb 0.000000\n", + "outstanding 0.001640\n", + "phenomenal 0.002292\n", + "fantastic 0.003796\n", + "terrific 0.004489\n", "dtype: float64" ] }, - "execution_count": 25, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb20, distfunc=vsm.cosine).head()" + "vsm.neighbors('superb', yelp20, distfunc=vsm.cosine).head()" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000\n", - ". 0.102634\n", - "

0.127549\n", - "

0.130171\n", - "pretty 0.130454\n", + "superb 0.000000\n", + "brilliant 0.006357\n", + "wild 0.009935\n", + "johnny 0.010105\n", + "ben 0.010140\n", "dtype: float64" ] }, - "execution_count": 26, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vsm.neighbors('superb', giga20, distfunc=vsm.cosine).head()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "superb 6.707879e-09\n", + "brilliant 3.591009e-02\n", + "wild 4.490683e-02\n", + "johnny 4.529075e-02\n", + "ben 4.536746e-02\n", + "dtype: float64" + ] + }, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', giga20, distfunc=vsm.cosine).head()" + "vsm.neighbors('superb', giga20, distfunc=proper_cosine).head()" ] }, { @@ -937,7 +1078,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -947,7 +1088,7 @@ " [1.06, 0.71]])" ] }, - "execution_count": 27, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -971,70 +1112,70 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ - "imdb5_oe = vsm.observed_over_expected(imdb5)" + "yelp5_oe = vsm.observed_over_expected(yelp5)" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ - "imdb20_oe = vsm.observed_over_expected(imdb20)" + "yelp20_oe = vsm.observed_over_expected(yelp20)" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000\n", - ". 0.716910\n", - "movie 0.791847\n", - "film 0.825658\n", - "measure 0.852617\n", + "superb 0.000000\n", + "excellent 0.338103\n", + "outstanding 0.344025\n", + "fantastic 0.367387\n", + "amazing 0.375123\n", "dtype: float64" ] }, - "execution_count": 30, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb5_oe).head()" + "vsm.neighbors('superb', yelp5_oe).head()" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000\n", - ". 0.081301\n", - "movie 0.083552\n", - "br 0.086846\n", - "film 0.102811\n", + "superb 0.000000\n", + "fantastic 0.140423\n", + "excellent 0.141790\n", + "outstanding 0.162165\n", + "amazing 0.165490\n", "dtype: float64" ] }, - "execution_count": 31, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb20_oe).head()" + "vsm.neighbors('superb', yelp20_oe).head()" ] }, { @@ -1066,75 +1207,75 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ - "imdb5_pmi = vsm.pmi(imdb5)" + "yelp5_pmi = vsm.pmi(yelp5)" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ - "imdb20_pmi = vsm.pmi(imdb20)" + "yelp20_pmi = vsm.pmi(yelp20)" ] }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000\n", - "decent 0.671197\n", - "bad 0.701241\n", - "great 0.723905\n", - "excellent 0.729288\n", + "superb 0.000000\n", + "excellent 0.376514\n", + "outstanding 0.395687\n", + "fantastic 0.415840\n", + "phenomenal 0.437463\n", "dtype: float64" ] }, - "execution_count": 34, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb5_pmi).head()" + "vsm.neighbors('superb', yelp5_pmi).head()" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "good 0.000000\n", - "decent 0.487422\n", - "great 0.567846\n", - "pretty 0.570119\n", - "acting 0.588779\n", + "superb 0.000000\n", + "fantastic 0.287739\n", + "excellent 0.291412\n", + "outstanding 0.298514\n", + "phenomenal 0.340393\n", "dtype: float64" ] }, - "execution_count": 35, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('good', imdb20_pmi).head()" + "vsm.neighbors('superb', yelp20_pmi).head()" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -1143,27 +1284,27 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "market 0.000000\n", - "markets 0.209558\n", - "investors 0.233547\n", - "stocks 0.273131\n", - "stock 0.277641\n", + "superb 0.000000\n", + "excellent 0.367458\n", + "perfect 0.374185\n", + "terrific 0.381038\n", + "beautifully 0.388652\n", "dtype: float64" ] }, - "execution_count": 37, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "vsm.neighbors('market', giga20_pmi).head()" + "vsm.neighbors('superb', giga20_pmi).head()" ] }, { @@ -1208,43 +1349,43 @@ "\n", "[Bojanowski et al. (2016)](https://arxiv.org/abs/1607.04606) (the [fastText](https://fasttext.cc) team) explore a particularly straightforward approach to doing this: represent each word as the sum of the representations for the character-level n-grams it contains.\n", "\n", - "It is simple to derive character-level n-gram representations from our existing VSMs. The function `vsm.ngram_vsm` implements the basic step. Here, we create the 4-gram version of `imdb5`:" + "It is simple to derive character-level n-gram representations from our existing VSMs. The function `vsm.ngram_vsm` implements the basic step. Here, we create the 4-gram version of `yelp5`:" ] }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ - "imdb5_ngrams = vsm.ngram_vsm(imdb5, n=4)" + "yelp5_ngrams = vsm.ngram_vsm(yelp5, n=4)" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(9806, 5000)" + "(10382, 6000)" ] }, - "execution_count": 39, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "imdb5_ngrams.shape" + "yelp5_ngrams.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "This has the same column dimension as the `imdb5`, but the rows are expanded with all the 4-grams, including boundary symbols `` and ``. \n", + "This has the same column dimension as the `yelp5`, but the rows are expanded with all the 4-grams, including boundary symbols `` and ``. \n", "\n", "`vsm.character_level_rep` is a simple function for creating new word representations from the associated character-level ones. Many variations on that function are worth trying – for example, you could include the original word vector where available, change the aggregation method from `sum` to something else, use a real morphological parser instead of just n-grams, and so on." ] @@ -1258,7 +1399,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 45, "metadata": {}, "outputs": [ { @@ -1267,45 +1408,45 @@ "False" ] }, - "execution_count": 40, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "'superbly' in imdb5.index" + "'superbly' in yelp5.index" ] }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 46, "metadata": {}, "outputs": [], "source": [ - "superbly = vsm.character_level_rep(\"superbly\", imdb5_ngrams)" + "superbly = vsm.character_level_rep(\"superbly\", yelp5_ngrams)" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 47, "metadata": {}, "outputs": [], "source": [ - "superb = vsm.character_level_rep(\"superb\", imdb5_ngrams)" + "superb = vsm.character_level_rep(\"superb\", yelp5_ngrams)" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.1521908156071029" + "0.004362871833742066" ] }, - "execution_count": 43, + "execution_count": 48, "metadata": {}, "output_type": "execute_result" } @@ -1339,26 +1480,12 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 49, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Applications/anaconda3/envs/nlu/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 150 missing from current font.\n", - " font.set_text(s, 0.0, flags=flags)\n", - "/Applications/anaconda3/envs/nlu/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:176: RuntimeWarning: Glyph 150 missing from current font.\n", - " font.load_char(ord(s), flags=flags)\n", - "/Applications/anaconda3/envs/nlu/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 151 missing from current font.\n", - " font.set_text(s, 0.0, flags=flags)\n", - "/Applications/anaconda3/envs/nlu/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:176: RuntimeWarning: Glyph 151 missing from current font.\n", - " font.load_char(ord(s), flags=flags)\n" - ] - }, { "data": { - "image/png": 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"text/plain": [ "

" ] @@ -1370,7 +1497,7 @@ } ], "source": [ - "vsm.tsne_viz(imdb20_pmi, random_state=42)" + "vsm.tsne_viz(yelp20_pmi, output_filename=None, figsize=(40, 50), random_state=42)" ] } ], @@ -1391,7 +1518,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -1399,5 +1526,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/vsm_02_dimreduce.ipynb b/vsm_02_dimreduce.ipynb index 44a1a31..d4c7871 100644 --- a/vsm_02_dimreduce.ipynb +++ b/vsm_02_dimreduce.ipynb @@ -18,7 +18,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -128,8 +128,8 @@ "metadata": {}, "outputs": [], "source": [ - "imdb5 = pd.read_csv(\n", - " os.path.join(DATA_HOME, 'imdb_window5-scaled.csv.gz'), index_col=0)" + "yelp5 = pd.read_csv(\n", + " os.path.join(DATA_HOME, 'yelp_window5-scaled.csv.gz'), index_col=0)" ] }, { @@ -138,8 +138,8 @@ "metadata": {}, "outputs": [], "source": [ - "imdb20 = pd.read_csv(\n", - " os.path.join(DATA_HOME, 'imdb_window20-flat.csv.gz'), index_col=0)" + "yelp20 = pd.read_csv(\n", + " os.path.join(DATA_HOME, 'yelp_window20-flat.csv.gz'), index_col=0)" ] }, { @@ -249,7 +249,7 @@ " \n", " \n", " \n", - " gnarly\n", + " gnarly\n", " 1.0\n", " 0.0\n", " 1.0\n", @@ -258,7 +258,7 @@ " 0.0\n", " \n", " \n", - " wicked\n", + " wicked\n", " 0.0\n", " 1.0\n", " 0.0\n", @@ -267,7 +267,7 @@ " 0.0\n", " \n", " \n", - " awesome\n", + " awesome\n", " 1.0\n", " 1.0\n", " 1.0\n", @@ -276,7 +276,7 @@ " 0.0\n", " \n", " \n", - " lame\n", + " lame\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -285,7 +285,7 @@ " 1.0\n", " \n", " \n", - " terrible\n", + " terrible\n", " 0.0\n", " 0.0\n", " 0.0\n", @@ -452,11 +452,11 @@ { "data": { "text/plain": [ - "superb 0.000000\n", - ". 0.814956\n", - "e 0.889682\n", - "k 0.891759\n", - "g 0.894064\n", + "superb 0.000000\n", + "phenomenal 0.012159\n", + "outstanding 0.012170\n", + "fantastic 0.015080\n", + "terrific 0.016488\n", "dtype: float64" ] }, @@ -466,7 +466,7 @@ } ], "source": [ - "vsm.neighbors('superb', imdb5).head()" + "vsm.neighbors('superb', yelp5).head()" ] }, { @@ -482,7 +482,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb5_svd = vsm.lsa(imdb5, k=100)" + "yelp5_svd = vsm.lsa(yelp5, k=100)" ] }, { @@ -493,11 +493,11 @@ { "data": { "text/plain": [ - "superb 0.000000\n", - "notch 0.015580\n", - "talents 0.028776\n", - "poor 0.029328\n", - "voice 0.031802\n", + "superb 0.000000\n", + "outstanding 0.009402\n", + "phenomenal 0.009575\n", + "fantastic 0.012573\n", + "terrific 0.014234\n", "dtype: float64" ] }, @@ -507,7 +507,7 @@ } ], "source": [ - "vsm.neighbors('superb', imdb5_svd).head()" + "vsm.neighbors('superb', yelp5_svd).head()" ] }, { @@ -527,7 +527,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb5_pmi = vsm.pmi(imdb5, positive=False)" + "yelp5_pmi = vsm.pmi(yelp5, positive=False)" ] }, { @@ -536,7 +536,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb5_pmi_svd = vsm.lsa(imdb5_pmi, k=100)" + "yelp5_pmi_svd = vsm.lsa(yelp5_pmi, k=100)" ] }, { @@ -548,10 +548,10 @@ "data": { "text/plain": [ "superb 0.000000\n", - "outstanding 0.017650\n", - "terrific 0.021071\n", - "fantastic 0.033293\n", - "brilliant 0.050633\n", + "phenomenal 0.040337\n", + "outstanding 0.066857\n", + "terrific 0.068770\n", + "exceptional 0.077025\n", "dtype: float64" ] }, @@ -561,7 +561,7 @@ } ], "source": [ - "vsm.neighbors('superb', imdb5_pmi_svd).head()" + "vsm.neighbors('superb', yelp5_pmi_svd).head()" ] }, { @@ -815,14 +815,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 1000 of 1000; error is 225481.6171875" + "Finished epoch 100 of 100; error is 1713142.828125" ] } ], "source": [ - "glove_model = TorchGloVe()\n", + "glove_model = TorchGloVe(max_iter=100)\n", "\n", - "imdb5_glv = glove_model.fit(imdb5)" + "yelp5_glv = glove_model.fit(yelp5)" ] }, { @@ -840,7 +840,7 @@ { "data": { "text/plain": [ - "0.45756810520194907" + "0.3325295995303305" ] }, "execution_count": 28, @@ -849,7 +849,7 @@ } ], "source": [ - "glove_model.score(imdb5)" + "glove_model.score(yelp5)" ] }, { @@ -860,11 +860,11 @@ { "data": { "text/plain": [ - "superb 0.000000\n", - "excellent 0.073974\n", - "outstanding 0.085162\n", - "terrific 0.116188\n", - "fantastic 0.127726\n", + "superb 0.000000\n", + "famous 0.004735\n", + "knowledge 0.005022\n", + "express 0.005296\n", + "sea 0.005308\n", "dtype: float64" ] }, @@ -874,7 +874,7 @@ } ], "source": [ - "vsm.neighbors('superb', imdb5_glv).head()" + "vsm.neighbors('superb', yelp5_glv).head()" ] }, { @@ -966,14 +966,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "Finished epoch 100 of 100; error is 0.0013741686707362533" + "Finished epoch 100 of 100; error is 0.0015143733471632004" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Autoencoder evaluation MSE after 100 evaluations: 0.0007\n" + "Autoencoder evaluation MSE after 100 evaluations: 0.0008\n" ] } ], @@ -982,7 +982,8 @@ "\n", "_, _, ae = autoencoder_evaluation(max_iter=ae_max_iter)\n", "\n", - "print(\"Autoencoder evaluation MSE after {0} evaluations: {1:0.04f}\".format(ae_max_iter, ae))" + "print(\"Autoencoder evaluation MSE after {0} evaluations: {1:0.04f}\".format(\n", + " ae_max_iter, ae))" ] }, { @@ -1006,7 +1007,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb5_l2 = imdb5.apply(vsm.length_norm, axis=1)" + "yelp5_l2 = yelp5.apply(vsm.length_norm, axis=1)" ] }, { @@ -1018,13 +1019,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 28. Training loss did not improve more than tol=1e-05. Final error is 0.0009803352440940216." + "Stopping after epoch 28. Training loss did not improve more than tol=1e-05. Final error is 0.00036444047873374075." ] } ], "source": [ - "imdb5_l2_ae = TorchAutoencoder(\n", - " max_iter=100, hidden_dim=50, eta=0.001).fit(imdb5_l2)" + "yelp5_l2_ae = TorchAutoencoder(\n", + " max_iter=100, hidden_dim=50, eta=0.001).fit(yelp5_l2)" ] }, { @@ -1035,11 +1036,11 @@ { "data": { "text/plain": [ - "superb 0.000000\n", - "lizard 0.001003\n", - "fill 0.001045\n", - "concert 0.001068\n", - "gritty 0.001128\n", + "superb 0.000000\n", + "fantastic 0.000021\n", + "outstanding 0.000023\n", + "terrific 0.000025\n", + "phenomenal 0.000036\n", "dtype: float64" ] }, @@ -1049,14 +1050,14 @@ } ], "source": [ - "vsm.neighbors('superb', imdb5_l2_ae).head()" + "vsm.neighbors('superb', yelp5_l2_ae).head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "This is very slow and seems not to work all that well. To speed things up, one can first apply LSA or similar:" + "This is very slow and often seems not to work all that well. To speed things up, one can first apply LSA or similar:" ] }, { @@ -1065,7 +1066,7 @@ "metadata": {}, "outputs": [], "source": [ - "imdb5_l2_svd100 = vsm.lsa(imdb5_l2, k=100)" + "yelp5_l2_svd100 = vsm.lsa(yelp5_l2, k=100)" ] }, { @@ -1077,13 +1078,13 @@ "name": "stderr", "output_type": "stream", "text": [ - "Stopping after epoch 29. Training loss did not improve more than tol=1e-05. Final error is 0.0007643999852007255." + "Stopping after epoch 56. Training loss did not improve more than tol=1e-05. Final error is 0.0014757064345758408." ] } ], "source": [ - "imdb_l2_svd100_ae = TorchAutoencoder(\n", - " max_iter=1000, hidden_dim=50, eta=0.01).fit(imdb5_l2_svd100)" + "yelp_l2_svd100_ae = TorchAutoencoder(\n", + " max_iter=1000, hidden_dim=50, eta=0.01).fit(yelp5_l2_svd100)" ] }, { @@ -1095,10 +1096,10 @@ "data": { "text/plain": [ "superb 0.000000\n", - "outstanding 0.017357\n", - "terrific 0.035065\n", - "exceptional 0.036933\n", - "magnificent 0.052532\n", + "phenomenal 0.014526\n", + "outstanding 0.016242\n", + "fantastic 0.017960\n", + "terrific 0.022512\n", "dtype: float64" ] }, @@ -1108,7 +1109,7 @@ } ], "source": [ - "vsm.neighbors('superb', imdb_l2_svd100_ae).head()" + "vsm.neighbors('superb', yelp_l2_svd100_ae).head()" ] }, { @@ -1133,7 +1134,7 @@ "\n", "* Subword modeling ([reviewed briefly in the previous notebook](vsm_01_distributional.ipynb#Subword-information)) is increasingly yielding dividends. (It would already be central if most of NLP focused on languages with complex morphology!) Check out the papers at the Subword and Character-Level Models for NLP Workshops: [SCLeM 2017](https://sites.google.com/view/sclem2017/home), [SCLeM 2018](https://sites.google.com/view/sclem2018/home).\n", "\n", - "* Contextualized word representations have proven valuable in many contexts. These methods do not provide representations for individual words, but rather represent them in their linguistic context. This creates space for modeling how word senses vary depending on their context of use. We will study these methods later in the quarter, mainly in the context of identifying ways that might achieve better results on your projects." + "* Contextualized word representations have proven valuable in many contexts. These methods do not provide representations for individual words, but rather represent them in their linguistic context. This creates space for modeling how word senses vary depending on their context of use. See [vsm_04_contextualreps.ipynb](vsm_04_contextualreps.ipynb) for techniques for using such models to create VSMs like those explored above." ] } ], @@ -1154,7 +1155,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -1162,5 +1163,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/vsm_03_retrofitting.ipynb b/vsm_03_retrofitting.ipynb index 4f97d72..3c4a94b 100644 --- a/vsm_03_retrofitting.ipynb +++ b/vsm_03_retrofitting.ipynb @@ -18,7 +18,7 @@ "outputs": [], "source": [ "__author__ = \"Christopher Potts\"\n", - "__version__ = \"CS224u, Stanford, Fall 2020\"" + "__version__ = \"CS224u, Stanford, Spring 2021\"" ] }, { @@ -56,17 +56,17 @@ "source": [ "## Overview\n", "\n", - "* Thus far, all of the information in our word vectors has come solely from co-occurrences patterns in text. This information is often very easy to obtain – though one does need a __lot__ of text – and it is striking how rich the resulting representations can be.\n", + "Thus far, all of the information in our word vectors has come solely from co-occurrences patterns in text. This information is often very easy to obtain – though one does need a __lot__ of text – and it is striking how rich the resulting representations can be.\n", "\n", - "* Nonetheless, it seems clear that there is important information that we will miss this way – relationships that just aren't encoded at all in co-occurrences or that get distorted by such patterns. \n", + "Nonetheless, it seems clear that there is important information that we will miss this way – relationships that just aren't encoded at all in co-occurrences or that get distorted by such patterns. \n", "\n", - "* For example, it is probably straightforward to learn representations that will support the inference that all puppies are dogs (_puppy_ entails _dog_), but it might be difficult to learn that _dog_ entails _mammal_ because of the unusual way that very broad taxonomic terms like _mammal_ are used in text.\n", + "For example, it is probably straightforward to learn representations that will support the inference that all puppies are dogs (_puppy_ entails _dog_), but it might be difficult to learn that _dog_ entails _mammal_ because of the unusual way that very broad taxonomic terms like _mammal_ are used in text.\n", "\n", - "* The question then arises: how can we bring structured information – labels – into our representations? If we can do that, then we might get the best of both worlds: the ease of using co-occurrence data and the refinement that comes from using labeled data.\n", + "The question then arises: how can we bring structured information – labels – into our representations? If we can do that, then we might get the best of both worlds: the ease of using co-occurrence data and the refinement that comes from using labeled data.\n", "\n", - "* In this notebook, we look at one powerful method for doing this: the __retrofitting__ model of [Faruqui et al. 2016](http://www.aclweb.org/anthology/N15-1184). In this model, one learns (or just downloads) distributed representations for nodes in a knowledge graph and then updates those representations to bring connected nodes closer to each other.\n", + "In this notebook, we look at one powerful method for doing this: the __retrofitting__ model of [Faruqui et al. 2016](http://www.aclweb.org/anthology/N15-1184). In this model, one learns (or just downloads) distributed representations for nodes in a knowledge graph and then updates those representations to bring connected nodes closer to each other.\n", "\n", - "* This is an incredibly fertile idea; the final section of the notebook reviews some recent extensions, and new ones are likely appearing all the time." + "This is an incredibly fertile idea; the final section of the notebook reviews some recent extensions, and new ones are likely appearing all the time." ] }, { @@ -86,7 +86,6 @@ "metadata": {}, "outputs": [], "source": [ - "%matplotlib inline\n", "from collections import defaultdict\n", "from nltk.corpus import wordnet as wn\n", "import numpy as np\n", @@ -106,6 +105,17 @@ "data_home = 'data'" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "__Note__: To make full use of this notebook, you will need the NLTK data distribution – or, at the very least, its WordNet files. Anaconda comes with NLTK but not with its data distribution. To install that, open a Python interpreter and run \n", + "\n", + "```import nltk; nltk.download()```\n", + "\n", + "If you decide to download the data to a different directory than the default, then you'll have to set `NLTK_DATA` in your shell profile. (If that doesn't make sense to you, then we recommend choosing the default download directory!)" + ] + }, { "cell_type": "markdown", "metadata": { @@ -236,7 +246,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -271,7 +281,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -306,7 +316,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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\n", 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\n", 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" ] @@ -639,7 +649,7 @@ } }, "source": [ - "You can now evaluate `X_retro` using the homework/bake-off notebook [hw_wordsim.ipynb](hw_wordsim.ipynb)!" + "You can now evaluate `X_retro` using the homework/bake-off notebook [hw_wordrelatedness.ipynb](hw_wordrelatedness.ipynb)!" ] }, { @@ -651,7 +661,8 @@ "# Optionally write `X_retro` to disk for use elsewhere:\n", "#\n", "# X_retro.to_csv(\n", - "# os.path.join(data_home, 'glove6B300d-retrofit-wn.csv.gz'), compression='gzip')" + "# os.path.join(data_home, 'glove6B300d-retrofit-wn.csv.gz'),\n", + "# compression='gzip')" ] }, { @@ -691,7 +702,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.4" + "version": "3.8.5" }, "widgets": { "state": {}, @@ -699,5 +710,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/vsm_04_contextualreps.ipynb b/vsm_04_contextualreps.ipynb new file mode 100644 index 0000000..7e7ead9 --- /dev/null +++ b/vsm_04_contextualreps.ipynb @@ -0,0 +1,1040 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Vector-space models: Static representations from contextual models" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "__author__ = \"Christopher Potts\"\n", + "__version__ = \"CS224u, Stanford, Spring 2021\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Contents\n", + "\n", + "1. [Overview](#Overview)\n", + "1. [General set-up](#General-set-up)\n", + "1. [Loading Transformer models](#Loading-Transformer-models)\n", + "1. [The basics of tokenizing](#The-basics-of-tokenizing)\n", + "1. [The basics of representations](#The-basics-of-representations)\n", + "1. [The decontextualized approach](#The-decontextualized-approach)\n", + " 1. [Basic example](#Basic-example)\n", + " 1. [Creating a full VSM](#Creating-a-full-VSM)\n", + "1. [The aggregated approach](#The-aggregated-approach)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Overview\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Can we get good static representations of words from models (like BERT) that supply only contextual representations? On the one hand, contextual models are very successful across a wide range of tasks, in large part because they are trained for a long time on a lot of data. This should be a boon for VSMs as we've designed them so far. On the other hand, the goal of having static representations might seem to be at odds with how these models process examples and represent examples. Part of the point is to obtain different representations for words depending on the context in which they occur, and a hallmark of the training procedure is that it processes sequences rather than individual words.\n", + "\n", + "[Bommasani et al. (2020)](https://www.aclweb.org/anthology/2020.acl-main.431) make a significant step forward in our understanding of these issues. Ultimately, they arrive at a positive answer: excellent static word representations can be obtained from contextual models. They explore two strategies for achieving this:\n", + "\n", + "1. __The decontextualized approach__: just process individual words as though they were isolated texts. Where a word consists of multiple tokens in the model, pool them with a function like mean or max.\n", + "1. __The aggregrated approach__: process lots and lots of texts containing the words of interest. As before, pool sub-word tokens, and also pool across all the pooled representations.\n", + "\n", + "As Bommasani et al. say, the decontextualized approach \"presents an unnatural input\" – these models were not trained on individual words, but rather on longer sequences, so the individual words are infrequent kinds of inputs at best (and unattested as far as the model is concerned if the special boundary tokens [CLS] and [SEP] are not included). However, in practice, Bommasani et al. achieve very impressive results with this approach on word similarity/relatedness tasks.\n", + "\n", + "The aggregrated approach is even better, but it requires more work and involves more decisions relating to which texts are processed.\n", + "\n", + "This notebook briefly explores both of these approaches, with the goal of making it easy for you to apply these methods in [the associated homework and bakeoff](hw_wordrelatedness.ipynb)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## General set-up\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import pandas as pd\n", + "import torch\n", + "from transformers import BertModel, BertTokenizer\n", + "from transformers import RobertaModel, RobertaTokenizer\n", + "\n", + "import utils\n", + "import vsm" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "DATA_HOME = os.path.join('data', 'vsmdata')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "utils.fix_random_seeds()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `transformers` library does a lot of logging. To avoid ending up with a cluttered notebook, I am changing the logging level. You might want to skip this as you scale up to building production systems, since the logging is very good – it gives you a lot of insights into what the models and code are doing." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import logging\n", + "logger = logging.getLogger()\n", + "logger.level = logging.ERROR" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading Transformer models\n", + "\n", + "To start, let's get a feel for the basic API that `transformers` provides. The first step is specifying the pretrained parameters we'll be using:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "bert_weights_name = 'bert-base-uncased'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There are lots other options for pretrained weights. See [this Hugging Face directory](https://huggingface.co/models)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we specify a tokenizer and a model that match both each other and our choice of pretrained weights:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "bert_tokenizer = BertTokenizer.from_pretrained(bert_weights_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "bert_model = BertModel.from_pretrained(bert_weights_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The basics of tokenizing" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "It's illuminating to see what the tokenizer does to example texts:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "example_text = \"Bert knows Snuffleupagus\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Simple tokenization:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['bert', 'knows', 's', '##nu', '##ffle', '##up', '##ag', '##us']" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bert_tokenizer.tokenize(example_text)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `encode` method maps individual strings to indices into the underlying embedding used by the model:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[101, 14324, 4282, 1055, 11231, 18142, 6279, 8490, 2271, 102]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ex_ids = bert_tokenizer.encode(example_text, add_special_tokens=True)\n", + "\n", + "ex_ids" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can get a better feel for what these representations are like by mapping the indices back to \"words\":" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['[CLS]',\n", + " 'bert',\n", + " 'knows',\n", + " 's',\n", + " '##nu',\n", + " '##ffle',\n", + " '##up',\n", + " '##ag',\n", + " '##us',\n", + " '[SEP]']" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bert_tokenizer.convert_ids_to_tokens(ex_ids)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Those are all the essential ingredients for working with these parameters in Hugging Face. Of course, the library has a lot of other functionality, but the above suffices for our current application." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The basics of representations" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To obtain the representations for a batch of examples, we use the `forward` method of the model, as follows:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "with torch.no_grad():\n", + " reps = bert_model(torch.tensor([ex_ids]), output_hidden_states=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The return value `reps` is a special `transformers` class that holds a lot of representations. If we want just the final output representations for each token, we use `last_hidden_state`:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([1, 10, 768])" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reps.last_hidden_state.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The shape indicates that our batch has 1 example, with 10 tokens, and each token is represented by a vector of dimensionality 768. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Aside: Hugging Face `transformers` models also have a `pooler_output` value. For BERT, this corresponds to the output representation above the [CLS] token, which is often used as a summary representation for the entire sequence. However, __we cannot use `pooler_output` in the current context__, as `transformers` adds new randomized parameters on top of it, to facilitate fine-tuning. If we want the [CLS] representation, we need to use `reps.last_hidden_state[:, 0]`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, if we want access to the output representations from each layer of the model, we use `hidden_states`. This will be `None` unless we set `output_hidden_states=True` when using the `forward` method, as above. " + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "13" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(reps.hidden_states)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The length 13 corresponds to the initial embedding layer (layer 0) and the 12 layers of this BERT model." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The final layer in `hidden_states` is identical to `last_hidden_state`:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([1, 10, 768])" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reps.hidden_states[-1].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "torch.equal(reps.hidden_states[-1], reps.last_hidden_state)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The decontextualized approach\n", + "\n", + "As discussed above, Bommasani et al. (2020) define and explore two general strategies for obtaining static representations for word using a model like BERT. The simpler one involves processing individual words and, where they correspond to multiple tokens, pooling those token representations into a single vector using an operation like mean." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Basic example" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To begin to see what this is like in practice, we'll use the method `vsm.hf_encode`, which maps texts to their ids, taking care to use `unk_token` for texts that can't otherwise be processed by the model." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Where a word corresponds to just one token in the vocabulary, it will get mapped to a single id:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['puppy']" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bert_tokenizer.tokenize('puppy')" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([[17022]])" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vsm.hf_encode(\"puppy\", bert_tokenizer)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we saw above, some words map to multiple tokens:" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['s', '##nu', '##ffle', '##up', '##ag', '##us']" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "bert_tokenizer.tokenize('snuffleupagus')" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "tensor([[ 1055, 11231, 18142, 6279, 8490, 2271]])" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subtok_ids = vsm.hf_encode(\"snuffleupagus\", bert_tokenizer)\n", + "\n", + "subtok_ids" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, the function `vsm.hf_represent` will map a batch of ids to their representations in a user-supplied model, at a specified layer in that model:" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([1, 6, 768])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subtok_reps = vsm.hf_represent(subtok_ids, bert_model, layer=-1)\n", + "\n", + "subtok_reps.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The shape here: 1 example containing 6 (sub-word) tokens, each of dimension 768. With `layer=-1`, we obtain the final output repreentation from the entire model." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The final step is to pool together the two tokens. Here, we can use a variety of operations; [Bommasani et al. 2020](https://www.aclweb.org/anthology/2020.acl-main.431) find that `mean` is the best overall:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([1, 768])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "subtok_pooled = vsm.mean_pooling(subtok_reps)\n", + "\n", + "subtok_pooled.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The function `vsm.mean_pooling` is simple `torch.mean` with `axis=1`. There are also predefined functions `vsm.max_pooling`, `vsm.min_pooling`, and `vsm.last_pooling` (representation for the final token)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Creating a full VSM\n", + "\n", + "Now we want to scale the above process to a large vocabulary, so that we can create a full VSM. The function `vsm.create_subword_pooling_vsm` makes this easy. To start, we get the vocabulary from one of our count VSMs (all of which have the same vocabulary):" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "vsm_index = pd.read_csv(\n", + " os.path.join(DATA_HOME, 'yelp_window5-scaled.csv.gz'),\n", + " usecols=[0], index_col=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [], + "source": [ + "vocab = list(vsm_index.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['):', ');', '..', '...', ':(']" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "vocab[: 5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And then we use `vsm.create_subword_pooling_vsm`:" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 2min 20s, sys: 2.12 s, total: 2min 22s\n", + "Wall time: 2min 22s\n" + ] + } + ], + "source": [ + "%%time\n", + "pooled_df = vsm.create_subword_pooling_vsm(\n", + " vocab, bert_tokenizer, bert_model, layer=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The result, `pooled_df`, is a `pd.DataFrame` with its index given by `vocab`. This can be used directly in the word relatedness evaluations that are central the homework and associated bakeoff." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(6000, 768)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pooled_df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " 0 1 2 3 4\n", + "): -0.576097 0.310341 -0.532733 -0.833050 -0.626199\n", + "); -0.056739 0.058793 -0.243109 -0.800296 -0.119222\n", + ".. -0.271509 -0.009211 -0.190293 -0.275234 -0.276218\n", + "... -0.380597 -0.054661 -0.161327 -0.299695 -0.299188\n", + ":( -0.425129 0.215213 -1.130576 -1.066704 -0.371664" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pooled_df.iloc[: 5, :5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This approach, and the associated code, should work generally for all Hugging Face Transformer-based models. Bommasani et al. (2020) provide a lot of guidance when it comes to how the model, the layer choice, and the pooling function interact." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The aggregated approach" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The aggregated is also straightfoward to implement given the above tool. To start, we can create a map from vocabulary items into their sequences of ids:" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "vocab_ids = {w: vsm.hf_encode(w, bert_tokenizer)[0] for w in vocab}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, let's assume we have a corpus of texts that contain the words of interest:" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "corpus = [\n", + " \"This is a sailing example\",\n", + " \"It's fun to go sailing!\",\n", + " \"We should go sailing.\",\n", + " \"I'd like to go sailing and sailing\",\n", + " \"This is merely an example\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The following embeds every corpus example, keeping `layer=1` representations:" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "corpus_ids = [vsm.hf_encode(text, bert_tokenizer)\n", + " for text in corpus]" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "corpus_reps = [vsm.hf_represent(ids, bert_model, layer=1)\n", + " for ids in corpus_ids]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally, we define a convenience function for finding all the occurrences of a sublist in a larger list:" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "def find_sublist_indices(sublist, mainlist):\n", + " indices = []\n", + " length = len(sublist)\n", + " for i in range(0, len(mainlist)-length+1):\n", + " if mainlist[i: i+length] == sublist:\n", + " indices.append((i, i+length))\n", + " return indices" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For example:" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[(0, 2), (4, 6)]" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "find_sublist_indices([1,2], [1, 2, 3, 0, 1, 2, 3])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And here's an example using our `vocab_ids` and `corpus`:" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "sailing = vocab_ids['sailing']" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "sailing_reps = []\n", + "\n", + "for ids, reps in zip(corpus_ids, corpus_reps):\n", + " offsets = find_sublist_indices(sailing, ids.squeeze(0))\n", + " for (start, end) in offsets:\n", + " pooled = vsm.mean_pooling(reps[:, start: end])\n", + " sailing_reps.append(pooled)\n", + "\n", + "sailing_rep = torch.mean(torch.cat(sailing_reps), axis=0).squeeze(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([768])" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sailing_rep.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The above building blocks could be used as the basis for an original system and bakeoff entry for this unit. The major question is probably which data to use for the corpus." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}