[GitHub] [beam] rezarokni commented on a diff in pull request #23035: Add one NER example to use a spaCy model with RunInference

[GitBox <gi...@apache.org>]

rezarokni commented on code in PR #23035:
URL: https://github.com/apache/beam/pull/23035#discussion_r963999768


##########
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:
   Please add documentation that explicitly calls out what the load() method is doing under the covers. Which I believes is:
   
   Per Python process ( of which a worker may have many ) downloads the file to a temporary location and then loads it into memory. 



-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: github-unsubscribe@beam.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org