liferoad commented on code in PR #23035:
URL: https://github.com/apache/beam/pull/23035#discussion_r964216653
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examples/notebooks/beam-ml/run_custom_inference.ipynb:
##########
@@ -0,0 +1,570 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "C1rAsD2L-hSO",
+ "metadata": {
+ "cellView": "form",
+ "id": "C1rAsD2L-hSO"
+ },
+ "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.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b6f8f3af-744e-4eaa-8a30-6d03e8e4d21e",
+ "metadata": {
+ "id": "b6f8f3af-744e-4eaa-8a30-6d03e8e4d21e"
+ },
+ "source": [
+ "# Bring your own Machine Leanring (ML) model to Beam RunInference\n",
+ "\n",
+ "<button>\n",
+ " <a
href=\"https://beam.apache.org/documentation/sdks/python-machine-learning/\";>\n",
+ " <img src=\"https://beam.apache.org/images/favicon.ico\";
alt=\"Open the docs\" height=\"16\"/>\n",
+ " Beam RunInference\n",
+ " </a>\n",
+ "</button>\n",
+ "\n",
+ "In this notebook, we walk through a simple example to show how to
build your own ML model handler using\n",
+
"[ModelHandler](https://beam.apache.org/releases/pydoc/current/apache_beam.ml.inference.base.html#apache_beam.ml.inference.base.ModelHandler).\n",
+ "\n",
+ "Named-Entity Recognition (NER) is one of the most common tasks for
Natural Language Processing (NLP), \n",
+ "which locates and classifies named entities in unstructured text into
pre-defined labels such as person name, organization, date, etc. \n",
+ "In this example, we illustrate how to use the popular spaCy package
to load a ML model and perform inference in a Beam pipeline using RunInference
PTransform.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "299af9bb-b2fc-405c-96e7-ee0a6ae24bdd",
+ "metadata": {
+ "id": "299af9bb-b2fc-405c-96e7-ee0a6ae24bdd"
+ },
+ "source": [
+ "## Package Dependencies\n",
+ "\n",
+ "The RunInference library is available in Apache Beam version
<b>2.40</b> or later.\n",
+ "\n",
+ "`spaCy` and `pandas` need to be installed. Here, a small NER model
(`en_core_web_sm`) is also installed but any valid spaCy model could be used."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "7f841596-f217-46d2-b64e-1952db4de4cb",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/";
+ },
+ "id": "7f841596-f217-46d2-b64e-1952db4de4cb",
+ "outputId": "da04ccb9-0801-47f6-ec9e-e87f0ca4569f"
+ },
+ "outputs": [],
+ "source": [
+ "# uncomment these to install the required packages\n",
+ "# %pip install spacy pandas\n",
+ "# %pip install \"apache-beam[gcp, dataframe, interactive]\"\n",
+ "# !python -m spacy download en_core_web_sm"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Let us play with spaCy first"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# create a spaCy language\n",
+ "\n",
+ "import spacy\n",
+ "\n",
+ "nlp = spacy.load(\"en_core_web_sm\")\n"
Review Comment:
Added more information. Done.
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