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<!DOCTYPE html>
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<p class="caption"><span class="caption-text">Beginner Tutorials</span></p>
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<li class="toctree-l1"><a class="reference internal" href="beginner/deep_learning_60min_blitz.html">Deep Learning with PyTorch: A 60 Minute Blitz</a><ul>
<li class="toctree-l2"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html">What is PyTorch?</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html#getting-started">Getting Started</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html#tensors">Tensors</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html#operations">Operations</a></li>
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<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html#numpy-bridge">Numpy Bridge</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html#converting-torch-tensor-to-numpy-array">Converting torch Tensor to numpy Array</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html#converting-numpy-array-to-torch-tensor">Converting numpy Array to torch Tensor</a></li>
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<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/tensor_tutorial.html#cuda-tensors">CUDA Tensors</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/blitz/autograd_tutorial.html">Autograd: automatic differentiation</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/autograd_tutorial.html#variable">Variable</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/autograd_tutorial.html#gradients">Gradients</a></li>
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<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/neural_networks_tutorial.html#define-the-network">Define the network</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/neural_networks_tutorial.html#loss-function">Loss Function</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/neural_networks_tutorial.html#backprop">Backprop</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/neural_networks_tutorial.html#update-the-weights">Update the weights</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html">Training a classifier</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#what-about-data">What about data?</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#training-an-image-classifier">Training an image classifier</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#loading-and-normalizing-cifar10">1. Loading and normalizing CIFAR10</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#define-a-convolution-neural-network">2. Define a Convolution Neural Network</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#define-a-loss-function-and-optimizer">3. Define a Loss function and optimizer</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#train-the-network">4. Train the network</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#test-the-network-on-the-test-data">5. Test the network on the test data</a></li>
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<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#training-on-gpu">Training on GPU</a></li>
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<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/cifar10_tutorial.html#where-do-i-go-next">Where do I go next?</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html">Optional: Data Parallelism</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#imports-and-parameters">Imports and parameters</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#dummy-dataset">Dummy DataSet</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#simple-model">Simple Model</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#create-model-and-dataparallel">Create Model and DataParallel</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#run-the-model">Run the Model</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#results">Results</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#gpus">2 GPUs</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#id1">3 GPUs</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#id2">8 GPUs</a></li>
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<li class="toctree-l3"><a class="reference internal" href="beginner/blitz/data_parallel_tutorial.html#summary">Summary</a></li>
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<li class="toctree-l4"><a class="reference internal" href="beginner/former_torchies/tensor_tutorial.html#converting-numpy-array-to-torch-tensor">Converting numpy Array to torch Tensor</a></li>
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<li class="toctree-l3"><a class="reference internal" href="beginner/former_torchies/tensor_tutorial.html#cuda-tensors">CUDA Tensors</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/former_torchies/autograd_tutorial.html">Autograd</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="beginner/former_torchies/autograd_tutorial.html#gradients">Gradients</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/former_torchies/nn_tutorial.html">nn package</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/former_torchies/nn_tutorial.html#example-1-convnet">Example 1: ConvNet</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/former_torchies/nn_tutorial.html#forward-and-backward-function-hooks">Forward and Backward Function Hooks</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/former_torchies/nn_tutorial.html#example-2-recurrent-net">Example 2: Recurrent Net</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/former_torchies/parallelism_tutorial.html">Multi-GPU examples</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/former_torchies/parallelism_tutorial.html#dataparallel">DataParallel</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/former_torchies/parallelism_tutorial.html#part-of-the-model-on-cpu-and-part-on-the-gpu">Part of the model on CPU and part on the GPU</a></li>
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<li class="toctree-l1"><a class="reference internal" href="beginner/pytorch_with_examples.html">Learning PyTorch with Examples</a><ul>
<li class="toctree-l2"><a class="reference internal" href="beginner/pytorch_with_examples.html#tensors">Tensors</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#warm-up-numpy">Warm-up: numpy</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#pytorch-tensors">PyTorch: Tensors</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/pytorch_with_examples.html#autograd">Autograd</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#pytorch-variables-and-autograd">PyTorch: Variables and autograd</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#pytorch-defining-new-autograd-functions">PyTorch: Defining new autograd functions</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#tensorflow-static-graphs">TensorFlow: Static Graphs</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/pytorch_with_examples.html#nn-module"><cite>nn</cite> module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#pytorch-nn">PyTorch: nn</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#pytorch-optim">PyTorch: optim</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#pytorch-custom-nn-modules">PyTorch: Custom nn Modules</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#pytorch-control-flow-weight-sharing">PyTorch: Control Flow + Weight Sharing</a></li>
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<li class="toctree-l2"><a class="reference internal" href="beginner/pytorch_with_examples.html#examples">Examples</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#id1">Tensors</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_tensor/two_layer_net_numpy.html">Warm-up: numpy</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_tensor/two_layer_net_tensor.html">PyTorch: Tensors</a></li>
</ul>
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<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#id2">Autograd</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_autograd/two_layer_net_autograd.html">PyTorch: Variables and autograd</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_autograd/two_layer_net_custom_function.html">PyTorch: Defining new autograd functions</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_autograd/tf_two_layer_net.html">TensorFlow: Static Graphs</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="beginner/pytorch_with_examples.html#id3"><cite>nn</cite> module</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_nn/two_layer_net_nn.html">PyTorch: nn</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_nn/two_layer_net_optim.html">PyTorch: optim</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_nn/two_layer_net_module.html">PyTorch: Custom nn Modules</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/examples_nn/dynamic_net.html">PyTorch: Control Flow + Weight Sharing</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="beginner/transfer_learning_tutorial.html">Transfer Learning tutorial</a><ul>
<li class="toctree-l2"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#load-data">Load Data</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#visualize-a-few-images">Visualize a few images</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#training-the-model">Training the model</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#visualizing-the-model-predictions">Visualizing the model predictions</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#finetuning-the-convnet">Finetuning the convnet</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#train-and-evaluate">Train and evaluate</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#convnet-as-fixed-feature-extractor">ConvNet as fixed feature extractor</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/transfer_learning_tutorial.html#id1">Train and evaluate</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="beginner/data_loading_tutorial.html">Data Loading and Processing Tutorial</a><ul>
<li class="toctree-l2"><a class="reference internal" href="beginner/data_loading_tutorial.html#dataset-class">Dataset class</a></li>
<li class="toctree-l2"><a class="reference internal" href="beginner/data_loading_tutorial.html#transforms">Transforms</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/data_loading_tutorial.html#compose-transforms">Compose transforms</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/data_loading_tutorial.html#iterating-through-the-dataset">Iterating through the dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="beginner/data_loading_tutorial.html#afterword-torchvision">Afterword: torchvision</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="beginner/deep_learning_nlp_tutorial.html">Deep Learning for NLP with Pytorch</a><ul>
<li class="toctree-l2"><a class="reference internal" href="beginner/nlp/pytorch_tutorial.html">Introduction to PyTorch</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/pytorch_tutorial.html#introduction-to-torch-s-tensor-library">Introduction to Torch’s tensor library</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/pytorch_tutorial.html#creating-tensors">Creating Tensors</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/pytorch_tutorial.html#operations-with-tensors">Operations with Tensors</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/pytorch_tutorial.html#reshaping-tensors">Reshaping Tensors</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/pytorch_tutorial.html#computation-graphs-and-automatic-differentiation">Computation Graphs and Automatic Differentiation</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html">Deep Learning with PyTorch</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#deep-learning-building-blocks-affine-maps-non-linearities-and-objectives">Deep Learning Building Blocks: Affine maps, non-linearities and objectives</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#affine-maps">Affine Maps</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#non-linearities">Non-Linearities</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#softmax-and-probabilities">Softmax and Probabilities</a></li>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#objective-functions">Objective Functions</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#optimization-and-training">Optimization and Training</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#creating-network-components-in-pytorch">Creating Network Components in Pytorch</a><ul>
<li class="toctree-l4"><a class="reference internal" href="beginner/nlp/deep_learning_tutorial.html#example-logistic-regression-bag-of-words-classifier">Example: Logistic Regression Bag-of-Words classifier</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/nlp/word_embeddings_tutorial.html">Word Embeddings: Encoding Lexical Semantics</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/word_embeddings_tutorial.html#getting-dense-word-embeddings">Getting Dense Word Embeddings</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/word_embeddings_tutorial.html#word-embeddings-in-pytorch">Word Embeddings in Pytorch</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/word_embeddings_tutorial.html#an-example-n-gram-language-modeling">An Example: N-Gram Language Modeling</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/word_embeddings_tutorial.html#exercise-computing-word-embeddings-continuous-bag-of-words">Exercise: Computing Word Embeddings: Continuous Bag-of-Words</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/nlp/sequence_models_tutorial.html">Sequence Models and Long-Short Term Memory Networks</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/sequence_models_tutorial.html#lstm-s-in-pytorch">LSTM’s in Pytorch</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/sequence_models_tutorial.html#example-an-lstm-for-part-of-speech-tagging">Example: An LSTM for Part-of-Speech Tagging</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/sequence_models_tutorial.html#exercise-augmenting-the-lstm-part-of-speech-tagger-with-character-level-features">Exercise: Augmenting the LSTM part-of-speech tagger with character-level features</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="beginner/nlp/advanced_tutorial.html">Advanced: Making Dynamic Decisions and the Bi-LSTM CRF</a><ul>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/advanced_tutorial.html#dynamic-versus-static-deep-learning-toolkits">Dynamic versus Static Deep Learning Toolkits</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/advanced_tutorial.html#bi-lstm-conditional-random-field-discussion">Bi-LSTM Conditional Random Field Discussion</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/advanced_tutorial.html#implementation-notes">Implementation Notes</a></li>
<li class="toctree-l3"><a class="reference internal" href="beginner/nlp/advanced_tutorial.html#exercise-a-new-loss-function-for-discriminative-tagging">Exercise: A new loss function for discriminative tagging</a></li>
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</ul>
<p class="caption"><span class="caption-text">Intermediate Tutorials</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html">Classifying Names with a Character-Level RNN</a><ul>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#preparing-the-data">Preparing the Data</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#turning-names-into-tensors">Turning Names into Tensors</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#creating-the-network">Creating the Network</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#training">Training</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#preparing-for-training">Preparing for Training</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#training-the-network">Training the Network</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#plotting-the-results">Plotting the Results</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#evaluating-the-results">Evaluating the Results</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#running-on-user-input">Running on User Input</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_classification_tutorial.html#exercises">Exercises</a></li>
</ul>
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<li class="toctree-l1"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html">Generating Names with a Character-Level RNN</a><ul>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#preparing-the-data">Preparing the Data</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#creating-the-network">Creating the Network</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#training">Training</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#preparing-for-training">Preparing for Training</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#training-the-network">Training the Network</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#plotting-the-losses">Plotting the Losses</a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#sampling-the-network">Sampling the Network</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/char_rnn_generation_tutorial.html#exercises">Exercises</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html">Translation with a Sequence to Sequence Network and Attention</a><ul>
<li class="toctree-l2"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#loading-data-files">Loading data files</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#the-seq2seq-model">The Seq2Seq Model</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#the-encoder">The Encoder</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#the-decoder">The Decoder</a><ul>
<li class="toctree-l4"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#simple-decoder">Simple Decoder</a></li>
<li class="toctree-l4"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#attention-decoder">Attention Decoder</a></li>
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<li class="toctree-l2"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#training">Training</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#preparing-training-data">Preparing Training Data</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#training-the-model">Training the Model</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#plotting-results">Plotting results</a></li>
</ul>
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<li class="toctree-l2"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#evaluation">Evaluation</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#training-and-evaluating">Training and Evaluating</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#visualizing-attention">Visualizing Attention</a></li>
</ul>
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<li class="toctree-l2"><a class="reference internal" href="intermediate/seq2seq_translation_tutorial.html#exercises">Exercises</a></li>
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<li class="toctree-l1"><a class="reference internal" href="intermediate/reinforcement_q_learning.html">Reinforcement Learning (DQN) tutorial</a><ul>
<li class="toctree-l2"><a class="reference internal" href="intermediate/reinforcement_q_learning.html#replay-memory">Replay Memory</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/reinforcement_q_learning.html#dqn-algorithm">DQN algorithm</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/reinforcement_q_learning.html#q-network">Q-network</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/reinforcement_q_learning.html#input-extraction">Input extraction</a></li>
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<li class="toctree-l2"><a class="reference internal" href="intermediate/reinforcement_q_learning.html#training">Training</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/reinforcement_q_learning.html#hyperparameters-and-utilities">Hyperparameters and utilities</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/reinforcement_q_learning.html#training-loop">Training loop</a></li>
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<li class="toctree-l1"><a class="reference internal" href="intermediate/dist_tuto.html">Writing Distributed Applications with PyTorch</a><ul>
<li class="toctree-l2"><a class="reference internal" href="intermediate/dist_tuto.html#setup">Setup</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/dist_tuto.html#point-to-point-communication">Point-to-Point Communication</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/dist_tuto.html#collective-communication">Collective Communication</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/dist_tuto.html#distributed-training">Distributed Training</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/dist_tuto.html#our-own-ring-allreduce">Our Own Ring-Allreduce</a></li>
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<li class="toctree-l2"><a class="reference internal" href="intermediate/dist_tuto.html#advanced-topics">Advanced Topics</a><ul>
<li class="toctree-l3"><a class="reference internal" href="intermediate/dist_tuto.html#communication-backends">Communication Backends</a></li>
<li class="toctree-l3"><a class="reference internal" href="intermediate/dist_tuto.html#initialization-methods">Initialization Methods</a></li>
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<li class="toctree-l1"><a class="reference internal" href="intermediate/spatial_transformer_tutorial.html">Spatial Transformer Networks Tutorial</a><ul>
<li class="toctree-l2"><a class="reference internal" href="intermediate/spatial_transformer_tutorial.html#loading-the-data">Loading the data</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/spatial_transformer_tutorial.html#depicting-spatial-transformer-networks">Depicting spatial transformer networks</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/spatial_transformer_tutorial.html#training-the-model">Training the model</a></li>
<li class="toctree-l2"><a class="reference internal" href="intermediate/spatial_transformer_tutorial.html#visualizing-the-stn-results">Visualizing the STN results</a></li>
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<p class="caption"><span class="caption-text">Advanced Tutorials</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="advanced/neural_style_tutorial.html">Neural Transfer with PyTorch</a><ul>
<li class="toctree-l2"><a class="reference internal" href="advanced/neural_style_tutorial.html#introduction">Introduction</a><ul>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#neural-what">Neural what?</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#how-does-it-work">How does it work?</a><ul>
<li class="toctree-l4"><a class="reference internal" href="advanced/neural_style_tutorial.html#ok-how-does-it-work">OK. How does it work?</a></li>
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<li class="toctree-l2"><a class="reference internal" href="advanced/neural_style_tutorial.html#pytorch-implementation">PyTorch implementation</a><ul>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#packages">Packages</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#cuda">Cuda</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#load-images">Load images</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#display-images">Display images</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#content-loss">Content loss</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#style-loss">Style loss</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#load-the-neural-network">Load the neural network</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#input-image">Input image</a></li>
<li class="toctree-l3"><a class="reference internal" href="advanced/neural_style_tutorial.html#gradient-descent">Gradient descent</a></li>
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<li class="toctree-l1"><a class="reference internal" href="advanced/numpy_extensions_tutorial.html">Creating extensions using numpy and scipy</a><ul>
<li class="toctree-l2"><a class="reference internal" href="advanced/numpy_extensions_tutorial.html#parameter-less-example">Parameter-less example</a></li>
<li class="toctree-l2"><a class="reference internal" href="advanced/numpy_extensions_tutorial.html#parametrized-example">Parametrized example</a></li>
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<li class="toctree-l1"><a class="reference internal" href="advanced/super_resolution_with_caffe2.html">Transfering a model from PyTorch to Caffe2 and Mobile using ONNX</a><ul>
<li class="toctree-l2"><a class="reference internal" href="advanced/super_resolution_with_caffe2.html#transfering-srresnet-using-onnx">Transfering SRResNet using ONNX</a></li>
<li class="toctree-l2"><a class="reference internal" href="advanced/super_resolution_with_caffe2.html#running-the-model-on-mobile-devices">Running the model on mobile devices</a></li>
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<li class="toctree-l1"><a class="reference internal" href="advanced/c_extension.html">Custom C extensions for pytorch</a><ul>
<li class="toctree-l2"><a class="reference internal" href="advanced/c_extension.html#step-1-prepare-your-c-code">Step 1. prepare your C code</a></li>
<li class="toctree-l2"><a class="reference internal" href="advanced/c_extension.html#step-2-include-it-in-your-python-code">Step 2: Include it in your Python code</a></li>
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