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MarkDaoustTensorflow Cloud maintainers
MarkDaoust
authored and
Tensorflow Cloud maintainers
committed
Notebook cleanup for tensorflow_cloud
PiperOrigin-RevId: 374672565
1 parent f7336cb commit 00ed5ca

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-31
lines changed

‎g3doc/METADATA‎

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# Standard docs checks for tensorflow.org and friends.
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include_presubmit: "//depot/google3/third_party/py/tensorflow_docs/google/tensorflow.org.METADATA"
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}
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presubmit: {
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# Generally we save notebooks without output to avoid repo bloat.
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# and make reviews easier. THen we execute notebooks to test them
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# when building the site... That's not possible in this case. So these
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# notebooks require at least one output cell.
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path_expression: "....ipynb"
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check_contents: {
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failure_message:
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"TensorFlow cloud notebooks are not runnable in the tensorflow.org import"
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"pipeline. so these notebooks must be saved with at least one"
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"cell output, typically the `print(tfc.__version__)`"
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required_regexp: "\"output_type\":"
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}
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}

‎g3doc/tutorials/distributed_training_nasnet_with_tensorflow_cloud.ipynb‎

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"source": [
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"# Distributed training NasNet with tensorflow_cloud and Google Cloud\n",
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"\n",
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"This example is based on [Image classification via fine-tuning with EfficientNet](https://keras.io/examples/vision/image_classification_efficientnet_fine_tuning/) to demonstrate how to train a [NasNetMobile](https://keras.io/api/applications/nasnet/#nasnetmobile-function) model using [tensorflow_cloud](https://tensorflow.org/cloud) and Google Cloud Platform at scale using distributed training.\n",
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"\n",
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"\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/cloud/tutorials/distributed_training_nasnet_with_tensorflow_cloud.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
@@ -55,13 +53,22 @@
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" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/cloud/tutorials/distributed_training_nasnet_with_tensorflow_cloud.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/distributed_training_nasnet_with_tensorflow_cloud.ipynb\"\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/distributed_training_nasnet_with_tensorflow_cloud.ipynb\" target=\"blank\"\u003e\n",
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" \u003cimg width=\"90\" src=\"https://www.kaggle.com/static/images/site-logo.png\" alt=\"Kaggle logo\"\u003eRun in Kaggle\n",
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" \u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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"\u003c/table\u003e\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "U0rZvc_B8Ilk"
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},
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"source": [
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"This example is based on [Image classification via fine-tuning with EfficientNet](https://keras.io/examples/vision/image_classification_efficientnet_fine_tuning/) to demonstrate how to train a [NasNetMobile](https://keras.io/api/applications/nasnet/#nasnetmobile-function) model using [tensorflow_cloud](https://tensorflow.org/cloud) and Google Cloud Platform at scale using distributed training."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "kA1D8jB3TviQ"
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.1.15\n"
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]
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}
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],
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"source": [
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"! pip install -q tensorflow-cloud\n",
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"\n",

‎g3doc/tutorials/google_cloud_project_setup_instructions.ipynb‎

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"source": [
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"# Setting Up and Connecting To Your Google Cloud Account\n",
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"\n",
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"This guide is to help first time users set up a Google Cloud Platform account specifically with the intention to use [tensorflow_cloud](https://tensorflow.org/cloud) to easily run training at scale on Google Cloud AI Platform. [TensorFlow Cloud](https://tensorflow.org/cloud) provides APIs that allow users to easily go from debugging, training, tuning Keras and TensorFlow code in a local or kaggle environment to distributed training/tuning on Cloud.\n",
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"\n",
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"\n",
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"\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/cloud/tutorials/google_cloud_project_setup_instructions.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
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" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/cloud/tutorials/google_cloud_project_setup_instructions.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/google_cloud_project_setup_instructions.ipynb\"\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/google_cloud_project_setup_instructions.ipynb\" target=\"blank\"\u003e\n",
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" \u003cimg width=\"90\" src=\"https://www.kaggle.com/static/images/site-logo.png\" alt=\"Kaggle logo\"\u003eRun in Kaggle\n",
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" \u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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"\u003c/table\u003e\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "vXUkgQhef4Op"
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},
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"source": [
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"This guide is to help first time users set up a Google Cloud Platform account specifically with the intention to use [tensorflow_cloud](https://tensorflow.org/cloud) to easily run training at scale on Google Cloud AI Platform. [TensorFlow Cloud](https://tensorflow.org/cloud) provides APIs that allow users to easily go from debugging, training, tuning Keras and TensorFlow code in a local or kaggle environment to distributed training/tuning on Cloud."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "yE1gpL8oUdV8"
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Your GCP_PROJECT_ID is: YOUR_PROJECT_ID\n",
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"Your SERVICE_ACCOUNT_NAME is: YOUR_SERVICE_ACCOUNT_NAME\n",
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"Your BUCKET_NAME is: YOUR_BUCKET_NAME\n"
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]
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}
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],
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"source": [
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"print(f\"Your GCP_PROJECT_ID is: {GCP_PROJECT_ID}\")\n",
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"print(f\"Your GCP_PROJECT_ID is: {GCP_PROJECT_ID}\")\n",
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"print(f\"Your SERVICE_ACCOUNT_NAME is: {SERVICE_ACCOUNT_NAME}\")\n",
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"print(f\"Your BUCKET_NAME is: {BUCKET_NAME}\")"
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"print(f\"Your BUCKET_NAME is: {BUCKET_NAME}\")"
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]
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}
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],

‎g3doc/tutorials/hp_tuning_cifar10_using_google_cloud.ipynb‎

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"id": "ztj7SjzXyu0p"
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},
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"source": [
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"# HP Tuning CIFAR10 on Google Cloud with tensorflow_cloud and CloudTuner\n",
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"\n",
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"This example is based on [Keras-Tuner CIFAR10 sample](https://github.com/keras-team/keras-tuner/blob/master/examples/cifar10.py) to demonstrate how to run HP tuning jobs using\n",
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"[TensorFlow Cloud](https://tensorflow.org/cloud) and Google Cloud Platform at scale.\n",
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"# HP Tuning on Google Cloud with CloudTuner\n",
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"\n",
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"\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/cloud/tutorials/hp_tuning_cifar10_using_google_cloud.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/hp_tuning_cifar10_using_google_cloud.ipynb\"\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/hp_tuning_cifar10_using_google_cloud.ipynb\" target=\"blank\"\u003e\n",
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" \u003cimg width=\"90\" src=\"https://www.kaggle.com/static/images/site-logo.png\" alt=\"Kaggle logo\"\u003eRun in Kaggle\n",
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" \u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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"\u003c/table\u003e\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "8g27bt9Ug4aQ"
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},
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"source": [
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"This example is based on [Keras-Tuner CIFAR10 sample](https://github.com/keras-team/keras-tuner/blob/master/examples/cifar10.py) to demonstrate how to run HP tuning jobs using\n",
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"[TensorFlow Cloud](https://tensorflow.org/cloud) and Google Cloud Platform at scale.\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "a751fAMsyu0q"
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.1.15\n"
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]
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}
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],
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"source": [
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"import datetime\n",
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"import uuid\n",

‎g3doc/tutorials/hp_tuning_wide_and_deep_model.ipynb‎

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"source": [
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"# Tuning a wide and deep model using Google Cloud\n",
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"\n",
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"In this example we will use CloudTuner and Google Cloud to Tune a [Wide and Deep Model](https://ai.googleblog.com/2016/06/wide-deep-learning-better-together-with.html) based on the tunable model introduced in [structured data learning with Wide, Deep, and Cross networks](https://keras.io/examples/structured_data/wide_deep_cross_networks/). In this example we will use the data set from [CAIIS Dogfood Day](https://www.kaggle.com/c/caiis-dogfood-day-2020/overview)\n",
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"\n",
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"\n",
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"\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/cloud/tutorials/hp_tuning_wide_and_deep_model.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
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" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/cloud/tutorials/hp_tuning_wide_and_deep_model.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/hp_tuning_wide_and_deep_model.ipynb\"\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/hp_tuning_wide_and_deep_model.ipynb\" target=\"blank\"\u003e\n",
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" \u003cimg width=\"90\" src=\"https://www.kaggle.com/static/images/site-logo.png\" alt=\"Kaggle logo\"\u003eRun in Kaggle\n",
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" \u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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"\u003c/table\u003e\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "Er9btVIUkjEq"
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},
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"source": [
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"\n",
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"In this example we will use CloudTuner and Google Cloud to Tune a [Wide and Deep Model](https://ai.googleblog.com/2016/06/wide-deep-learning-better-together-with.html) based on the tunable model introduced in [structured data learning with Wide, Deep, and Cross networks](https://keras.io/examples/structured_data/wide_deep_cross_networks/). In this example we will use the data set from [CAIIS Dogfood Day](https://www.kaggle.com/c/caiis-dogfood-day-2020/overview)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "dzyeZrh9C99v"
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"id": "dzyeZrh9C99v",
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"outputId": "353637ca-a7d4-4d49-c030-dcbb103355bb"
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.1.15\n"
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]
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}
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],
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"source": [
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"import datetime\n",
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"import uuid\n",
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],
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"metadata": {
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"colab": {
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"collapsed_sections": [
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"aaHrkvhUm7hD"
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],
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"collapsed_sections": [],
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"name": "hp_tuning_wide_and_deep_model.ipynb",
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"provenance": [],
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"toc_visible": true
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},
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"kernelspec": {

‎g3doc/tutorials/overview.ipynb‎

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"source": [
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"# TensorFlow Cloud\n",
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"\n",
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"TensorFlow Cloud is a library that makes it easier to do training and hyperparameter tuning of Keras models on Google Cloud.\n",
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"\n",
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"\n",
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"\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/cloud/tutorials/overview.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
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" \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/cloud/tutorials/overview.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/overview.ipynb\"\u003e\n",
56+
" \u003ca href=\"https://kaggle.com/kernels/welcome?src=https://github.com/tensorflow/cloud/blob/master/g3doc/tutorials/overview.ipynb\" target=\"blank\"\u003e\n",
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" \u003cimg width=\"90\" src=\"https://www.kaggle.com/static/images/site-logo.png\" alt=\"Kaggle logo\"\u003eRun in Kaggle\n",
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" \u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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"\u003c/table\u003e\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "mU84TfyShbqm"
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},
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"source": [
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"TensorFlow Cloud is a library that makes it easier to do training and hyperparameter tuning of Keras models on Google Cloud.\n"
70+
]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"metadata": {
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"id": "kA1D8jB3TviQ"
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.1.15\n"
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]
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}
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],
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"source": [
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"! pip install -q tensorflow-cloud\n",
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"import tensorflow_cloud as tfc\n",

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