Create TFX Example.ipynb

samples/tfx-oss/TFX Example.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# TFX on KubeFlow Pipelines Example\n",
+    "\n",
+    "### Install TFX and KFP packages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip3 install https://storage.googleapis.com/ml-pipeline/tfx/tfx-0.12.0rc0-py2.py3-none-any.whl \n",
+    "!pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.10/kfp.tar.gz --upgrade\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Get the TFX repo with sample pipeline\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!git clone https://github.com/tensorflow/tfx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# copy the trainer code to a storage bucket \n",
+    "!gsutil cp tfx/examples/chicago_taxi_pipeline/taxi_utils.py gs://<my bucket>/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Configure the TFX pipeline example\n",
+    "\n",
+    "Reload this cell by running the load command to get the pipeline configuration file\n",
+    "```\n",
+    "%load tfx/examples/chicago_taxi_pipeline/taxi_pipeline_kubeflow.py\n",
+    "```\n",
+    "\n",
+    "Configure:\n",
+    "- GCS storage bucket name (replace my-bucket)\n",
+    "- GCP project ID (replace my-gcp-project)\n",
+    "- Make sure the path to the taxi_utils.py is correct\n",
+    "\n",
+    "The dataset in BigQuery has 100M rows, you can change the query parameters in WHERE clause to limit the number of rows used.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load tfx/examples/chicago_taxi_pipeline/taxi_pipeline_kubeflow.py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compile the pipeline and submit a run to the Kubeflow cluster"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get or create a new experiment\n",
+    "import kfp\n",
+    "client = kfp.Client()\n",
+    "experiment = client.create_experiment(\"TFX Examples\")\n",
+    "pipeline_filename = \"chicago_taxi_pipeline_kubeflow.tar.gz\"\n",
+    "\n",
+    "#Submit a pipeline run\n",
+    "run_name = 'Run 1'\n",
+    "run_result = client.run_pipeline(experiment.id, run_name, pipeline_filename, {})\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": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}