jaxpr commented on code in PR #25904:
URL: https://github.com/apache/beam/pull/25904#discussion_r1155892121
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examples/notebooks/beam-ml/run_inference_xgboost.ipynb:
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@@ -0,0 +1,321 @@
+{
+ "nbformat": 4,
+ "nbformat_minor": 0,
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "name": "python3",
+ "display_name": "Python 3"
+ },
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "cellView": "form",
+ "id": "XobBB6Sv8mB3"
+ },
+ "outputs": [],
+ "source": [
+ "# @title ###### Licensed to the Apache Software Foundation (ASF),
Version 2.0 (the \"License\")\n",
+ "\n",
+ "# Licensed to the Apache Software Foundation (ASF) under one\n",
+ "# or more contributor license agreements. See the NOTICE file\n",
+ "# distributed with this work for additional information\n",
+ "# regarding copyright ownership. The ASF licenses this file\n",
+ "# to you under the Apache License, Version 2.0 (the\n",
+ "# \"License\"); you may not use this file except in compliance\n",
+ "# with the License. You may obtain a copy of the License at\n",
+ "#\n",
+ "# http://www.apache.org/licenses/LICENSE-2.0\n";,
+ "#\n",
+ "# Unless required by applicable law or agreed to in writing,\n",
+ "# software distributed under the License is distributed on an\n",
+ "# \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n",
+ "# KIND, either express or implied. See the License for the\n",
+ "# specific language governing permissions and limitations\n",
+ "# under the License"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Apache Beam RunInference for XGBoost\n",
+ "\n",
+ "<table align=\"left\">\n",
+ " <td>\n",
+ " <a target=\"_blank\"
href=\"https://colab.research.google.com/github/apache/beam/blob/master/examples/notebooks/beam-ml/run_inference_xgboost.ipynb\";><img
src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\";
/>Run in Google Colab</a>\n",
+ " </td>\n",
+ " <td>\n",
+ " <a target=\"_blank\"
href=\"https://github.com/apache/beam/blob/master/examples/notebooks/beam-ml/run_inference_xgboost.ipynb\";><img
src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\";
/>View source on GitHub</a>\n",
+ " </td>\n",
+ "</table>\n"
+ ],
+ "metadata": {
+ "id": "DUGbrRuv89CS"
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "This notebook demonstrates the use of the RunInference transform for
XGBoost. Apache Beam RunInference has implementations of the ModelHandler class
prebuilt for XGBoost. For more information about the RunInference API, see
Machine Learning in the Apache Beam documentation.\n",
+ "\n",
+ "You can choose the appropriate model handler based on your input data
type:\n",
+ "\n",
+ "- NumPy model handler\n",
+ "- Pandas DataFrame model handler\n",
+ "- Datatable model handler\n",
+ "- SciPy model handler\n",
+ "\n",
+ "With RunInference, these model handlers manage batching,
vectorization, and prediction optimization for your XGBoost pipeline or
model.\n",
+ "\n",
+ "This notebook demonstrates the following common RunInference
patterns:\n",
+ "\n",
+ "Generate predictions.\n",
+ "Postprocess results after RunInference.\n",
+ "One model to showcase classification of Iris flowers and one
regression model to showcase prediction of housing prices"
Review Comment:
I added some simple postprocessing to print the flowers' names and flatten
outputted batches.
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