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new 19514938176 Add RunInference example for TensorFlow Hub pre-trained
model (#24529)
19514938176 is described below
commit 1951493817638f75bcf03e57a09cc934257cb31a
Author: harrisonlimh <97203667+harrisonl...@users.noreply.github.com>
AuthorDate: Tue Dec 6 11:23:22 2022 -0800
Add RunInference example for TensorFlow Hub pre-trained model (#24529)
* Create run_inference_tensorflow_hub.ipynb
Add a notebook for using RunInference() with a TensorFlow Hub model.
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
* Update run_inference_tensorflow_hub.ipynb
---
.../beam-ml/run_inference_tensorflow_hub.ipynb | 543 +++++++++++++++++++++
1 file changed, 543 insertions(+)
diff --git a/examples/notebooks/beam-ml/run_inference_tensorflow_hub.ipynb
b/examples/notebooks/beam-ml/run_inference_tensorflow_hub.ipynb
new file mode 100644
index 00000000000..77007f72efc
--- /dev/null
+++ b/examples/notebooks/beam-ml/run_inference_tensorflow_hub.ipynb
@@ -0,0 +1,543 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "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"
+ ],
+ "metadata": {
+ "id": "Qx4wHX2zIKS1",
+ "cellView": "form"
+ },
+ "id": "Qx4wHX2zIKS1",
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "3ac8fc4a-a0ef-47b9-bd80-10801eebe13e"
+ },
+ "source": [
+ "# RunInference with Sentence-T5 (ST5) model\n",
+ "\n",
+ "This example demonstrates the use of the RunInference transform with
the pre-trained [ST5 text encoder
model](https://tfhub.dev/google/sentence-t5/st5-base/1) from TensorFlow Hub.
The transform runs locally using the [Interactive
Runner](https://beam.apache.org/releases/pydoc/2.11.0/apache_beam.runners.interactive.interactive_runner.html)."
+ ],
+ "id": "3ac8fc4a-a0ef-47b9-bd80-10801eebe13e"
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "3402ecc9-28d6-4226-99b1-147a2d23b7a9"
+ },
+ "source": [
+ "## Download and install the dependencies\n"
+ ],
+ "id": "3402ecc9-28d6-4226-99b1-147a2d23b7a9"
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!pip install apache_beam[gcp,interactive]==2.41.0\n",
+ "!pip install tensorflow==2.10.0\n",
+ "!pip install tensorflow_text==2.10.0\n",
+ "!pip install keras==2.10.0\n",
+ "!pip install tfx_bsl==1.10.0\n",
+ "!pip install pillow==8.4.0"
+ ],
+ "metadata": {
+ "id": "H2-orNBqsZ95"
+ },
+ "id": "H2-orNBqsZ95",
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "f313a508-59ea-47ed-86eb-c9c8e67785f2",
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "import tensorflow as tf\n",
+ "import tensorflow_hub as hub\n",
+ "import tensorflow_text\n",
+ "\n",
+ "from tensorflow import keras\n",
+ "\n",
+ "import apache_beam as beam\n",
+ "import apache_beam.runners.interactive.interactive_beam as ib\n",
+ "\n",
+ "from apache_beam.ml.inference.base import RunInference\n",
+ "from apache_beam.ml.inference.base import ModelHandler\n",
+ "from apache_beam.runners.interactive.interactive_runner import
InteractiveRunner\n",
+ "\n",
+ "from tfx_bsl.public.beam.run_inference import CreateModelHandler\n",
+ "from tfx_bsl.public.proto import model_spec_pb2"
+ ],
+ "id": "f313a508-59ea-47ed-86eb-c9c8e67785f2"
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Authenticate with Google Cloud\n",
+ "This notebook relies on saving the model to Google Cloud. To use your
Google Cloud account, authenticate this notebook."
+ ],
+ "metadata": {
+ "id": "6zAnF4EmomUS"
+ },
+ "id": "6zAnF4EmomUS"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "r1fgn5I_-mzA"
+ },
+ "outputs": [],
+ "source": [
+ "from google.colab import auth\n",
+ "auth.authenticate_user()"
+ ],
+ "id": "r1fgn5I_-mzA"
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "74db0203-3d26-4bc4-8271-81fad9756297"
+ },
+ "source": [
+ "## Create a Keras Model from TensorFlow Hub image\n",
+ "\n",
+ "Replace `GCS_BUCKET` with the name of your bucket. Your model will be
saved in `MODEL_EXPORT_DIR`."
+ ],
+ "id": "74db0203-3d26-4bc4-8271-81fad9756297"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "2ff8e394-f577-4dea-bef9-a4f4528c1378"
+ },
+ "outputs": [],
+ "source": [
+ "GCS_BUCKET = '<GCS Bucket>'\n",
+ "\n",
+ "MODEL_EXPORT_DIR = f'gs://{GCS_BUCKET}/st5-base/1'"
+ ],
+ "id": "2ff8e394-f577-4dea-bef9-a4f4528c1378"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "ccaede25-1c1a-4ec4-9296-25c9a2ac43d7"
+ },
+ "outputs": [],
+ "source": [
+ "inp = tf.keras.layers.Input(shape=[], dtype=tf.string,
name='input')\n",
+ "hub_url = \"https://tfhub.dev/google/sentence-t5/st5-base/1\"\n";,
+ "imported = hub.KerasLayer(hub_url)\n",
+ "outp = imported(inp)\n",
+ "model = tf.keras.Model(inp, outp)"
+ ],
+ "id": "ccaede25-1c1a-4ec4-9296-25c9a2ac43d7"
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# The ST5 model returns a 768-dimensional vector for an English text
input.\n",
+ "model.summary()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/";
+ },
+ "id": "Xvb-E0D1JHnr",
+ "outputId": "121a5924-94b0-4b01-97da-14a7223ec61c"
+ },
+ "id": "Xvb-E0D1JHnr",
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Model: \"model\"\n",
+
"_________________________________________________________________\n",
+ " Layer (type) Output Shape Param #
\n",
+
"=================================================================\n",
+ " input (InputLayer) [(None,)] 0
\n",
+ "
\n",
+ " keras_layer (KerasLayer) [(None, 768)] 0
\n",
+ "
\n",
+
"=================================================================\n",
+ "Total params: 0\n",
+ "Trainable params: 0\n",
+ "Non-trainable params: 0\n",
+
"_________________________________________________________________\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "29803d5b-93b9-41fc-b414-f7c737c5d7bc"
+ },
+ "source": [
+ "## Save the model\n",
+ "Save the model with a TF function definition for RunInference."
+ ],
+ "id": "29803d5b-93b9-41fc-b414-f7c737c5d7bc"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "704abfca-5956-4fc1-9717-4c6d5bf2db8e"
+ },
+ "outputs": [],
+ "source": [
+ "RAW_DATA_PREDICT_SPEC = {\n",
+ " 'input': tf.io.FixedLenFeature([], tf.string),\n",
+ "}\n",
+ "\n",
+ "@tf.function(input_signature=[tf.TensorSpec(shape=[None],
dtype=tf.string)])\n",
+ "def call(serialized_examples):\n",
+ " features = tf.io.parse_example(serialized_examples,
RAW_DATA_PREDICT_SPEC)\n",
+ " return model(features)\n",
+ "\n",
+ "tf.saved_model.save(model, MODEL_EXPORT_DIR,
signatures={'serving_default': call})"
+ ],
+ "id": "704abfca-5956-4fc1-9717-4c6d5bf2db8e"
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "7b56569d-e540-44ed-a46a-9cec886522f6"
+ },
+ "source": [
+ "## Create and test the RunInference pipeline locally\n",
+ "Use TFX_BSL's
[CreateModelHandler](https://www.tensorflow.org/tfx/tfx_bsl/api_docs/python/tfx_bsl/public/beam/run_inference/CreateModelHandler)
function for RunInference with TensorFlow models."
+ ],
+ "id": "7b56569d-e540-44ed-a46a-9cec886522f6"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "fad13b30-b159-425c-8c15-a41301abd3a4"
+ },
+ "outputs": [],
+ "source": [
+ "# Creates a TensorFlow example to feed to the model handler.\n",
+ "class ExampleProcessor:\n",
+ " def create_example(self, feature: tf.string):\n",
+ " return tf.train.Example(\n",
+ " features=tf.train.Features(\n",
+ " feature={'input' :
self.create_feature(feature)})\n",
+ " )\n",
+ "\n",
+ " def create_feature(self, element: tf.string):\n",
+ " return
tf.train.Feature(bytes_list=tf.train.BytesList(value=[element.encode()], ))\n"
+ ],
+ "id": "fad13b30-b159-425c-8c15-a41301abd3a4"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "60380ebd-5bc8-4bc6-9cf4-3030bf687367",
+ "scrolled": true,
+ "colab": {
+ "base_uri": "https://localhost:8080/";,
+ "height": 17
+ },
+ "outputId": "1b53641d-806f-4f0b-c8f3-9badf67ab98a"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/javascript": [
+ "\n",
+ " if (typeof window.interactive_beam_jquery ==
'undefined') {\n",
+ " var jqueryScript =
document.createElement('script');\n",
+ " jqueryScript.src =
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+ " jqueryScript.type = 'text/javascript';\n",
+ " jqueryScript.onload = function() {\n",
+ " var datatableScript =
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+ " datatableScript.src =
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+ " document.head.appendChild(jqueryScript);\n",
+ " } else {\n",
+ "
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+ " \n",
+ " });\n",
+ " }"
+ ]
+ },
+ "metadata": {}
+ }
+ ],
+ "source": [
+ "saved_model_spec =
model_spec_pb2.SavedModelSpec(model_path=MODEL_EXPORT_DIR)\n",
+ "inferece_spec_type =
model_spec_pb2.InferenceSpecType(saved_model_spec=saved_model_spec)\n",
+ "model_handler = CreateModelHandler(inferece_spec_type)\n",
+ "\n",
+ "questions = [\n",
+ " 'what is the official slogan for the 2018 winter olympics?',\n",
+ "]\n",
+ "\n",
+ "pipeline = beam.Pipeline(InteractiveRunner())\n",
+ "\n",
+ "inference = (pipeline | 'CreateSentences' >>
beam.Create(questions)\n",
+ " | 'Convert input to Tensor' >> beam.Map(lambda x:
ExampleProcessor().create_example(x))\n",
+ " | 'RunInference with T5' >>
RunInference(model_handler))"
+ ],
+ "id": "60380ebd-5bc8-4bc6-9cf4-3030bf687367"
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "29a84182-baa5-45c4-abcf-d9cab84835c9",
+ "colab": {
+ "base_uri": "https://localhost:8080/";,
+ "height": 565
+ },
+ "outputId": "d6ef64c2-f120-4bc1-c972-78c1cd8a729e"
+ },
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ "\n",
+ " <link rel=\"stylesheet\"
href=\"https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css\";
integrity=\"sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh\"
crossorigin=\"anonymous\">\n",
+ " <div
id=\"progress_indicator_02aa6852261e6f1837821c6131548b47\">\n",
+ " <div class=\"spinner-border text-info\"
role=\"status\"></div>\n",
+ " <span class=\"text-info\">Processing...
show</span>\n",
+ " </div>\n",
+ " "
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "WARNING:tensorflow:From
/usr/local/lib/python3.8/dist-packages/tfx_bsl/beam/run_inference.py:615: load
(from tensorflow.python.saved_model.loader_impl) is deprecated and will be
removed in a future version.\n",
+ "Instructions for updating:\n",
+ "This function will only be available through the v1 compatibility
library as tf.compat.v1.saved_model.loader.load or
tf.compat.v1.saved_model.load. There will be a new function for importing
SavedModels in Tensorflow 2.0.\n",
+ "2022-12-06 09:30:47.084208: I
tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:354] MLIR V1
optimization pass is not enabled\n",
+ "2022-12-06 09:30:54.471173: I
tensorflow/compiler/xla/service/service.cc:173] XLA service 0x4a3e0a00
initialized for platform Host (this does not guarantee that XLA will be used).
Devices:\n",
+ "2022-12-06 09:30:54.471244: I
tensorflow/compiler/xla/service/service.cc:181] StreamExecutor device (0):
Host, Default Version\n",
+ "2022-12-06 09:30:54.537285: I
tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:268] disabling MLIR
crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.\n",
+ "2022-12-06 09:31:00.441479: I
tensorflow/compiler/jit/xla_compilation_cache.cc:476] Compiled cluster using
XLA! This line is logged at most once for the lifetime of the process.\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ "\n",
+ " <style>\n",
+ "
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+ " <link rel=\"stylesheet\"
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+ " <script>\n",
+ " \n",
+ " if (typeof window.interactive_beam_jquery ==
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+ " var jqueryScript =
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+ " jqueryScript.src =
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+ " }\n",
+ " </script>"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/javascript": [
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