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# Conflicts: # neural_structured_learning/research/gam/data/dataset.py # neural_structured_learning/research/gam/data/loaders.py # neural_structured_learning/research/gam/experiments/helper.py # neural_structured_learning/research/gam/experiments/run_train_gam.py # neural_structured_learning/research/gam/experiments/run_train_gam_graph.py # neural_structured_learning/research/gam/trainer/trainer_agreement.py # neural_structured_learning/research/gam/trainer/trainer_classification.py # neural_structured_learning/research/gam/trainer/trainer_cotrain.py
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‎README.md

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[[4] T. Miyato, S. Maeda, M. Koyama and S. Ishii. "Virtual Adversarial Training: a Regularization Method for Supervised and Semi-supervised Learning." ICLR 2016](https://arxiv.org/pdf/1704.03976.pdf)
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[[5] D. Juan, C. Lu, Z. Li, F. Peng, A. Timofeev, Y. Chen, Y. Gao, T. Duerig, A. Tomkins and S. Ravi "Graph-RISE: Graph-Regularized Image Semantic Embedding." arXiv 2019](https://arxiv.org/abs/1902.10814)
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[[5] D. Juan, C. Lu, Z. Li, F. Peng, A. Timofeev, Y. Chen, Y. Gao, T. Duerig, A. Tomkins and S. Ravi "Graph-RISE: Graph-Regularized Image Semantic Embedding." WSDM 2020](https://arxiv.org/abs/1902.10814)
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‎g3doc/tutorials/adversarial_keras_cnn_mnist.ipynb

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"id": "wfqlePz0g6o5"
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},
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"source": [
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"<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://www.tensorflow.org/neural_structured_learning/tutorials/adversarial_keras_cnn_mnist\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" />View on TensorFlow.org</a>\n",
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" </td>\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/adversarial_keras_cnn_mnist.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
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" </td>\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://github.com/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/adversarial_keras_cnn_mnist.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
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" </td>\n",
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"</table>"
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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/neural_structured_learning/tutorials/adversarial_keras_cnn_mnist\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/adversarial_keras_cnn_mnist.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003eRun in Google Colab\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/adversarial_keras_cnn_mnist.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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"\u003c/table\u003e"
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]
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},
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{
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"id": "m58k8nv3YVdf"
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},
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"source": [
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"Install Tensorflow 2.0 to create an interactive developing environment with\n",
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"Select TensorFlow 2.x to create an interactive development environment with\n",
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"eager execution."
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]
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},
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},
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"outputs": [],
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"source": [
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"!pip install tensorflow-gpu==2.0.0-rc0"
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"try:\n",
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" # %tensorflow_version only exists in Colab.\n",
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" %tensorflow_version 2.x\n",
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"except Exception:\n",
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" !pip install --quiet tensorflow-gpu>=2.0.0"
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]
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},
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{
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" x = tf.keras.layers.Conv2D(\n",
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" num_filters, hparams.kernel_size, activation='relu')(\n",
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" x)\n",
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" if i < len(hparams.conv_filters) - 1:\n",
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" if i \u003c len(hparams.conv_filters) - 1:\n",
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" # max pooling between convolutional layers\n",
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" x = tf.keras.layers.MaxPooling2D(hparams.pool_size)(x)\n",
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" x = tf.keras.layers.Flatten()(x)\n",
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"timestamp": 1566174674305
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}
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],
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"toc_visible": true,
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"version": "0.3.2"
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"toc_visible": true
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},
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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"nbformat": 4,

‎g3doc/tutorials/graph_keras_lstm_imdb.ipynb

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"source": [
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"## Requirements\n",
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"\n",
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"1. Install TensorFlow 2.x to create an interactive developing environment with eager execution.\n",
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"2. Install the Neural Structured Learning package.\n",
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"3. Install tensorflow-hub."
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"1. Select TensorFlow 2.x to create an interactive development environment with eager execution.\n",
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"2. Install the Neural Structured Learning package.\n",
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"3. Install tensorflow-hub."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 0,
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"metadata": {
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"colab": {},
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"colab_type": "code",
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"id": "yDUe7gk_ztZ-"
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},
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"outputs": [],
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"source": [
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"try:\n",
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" # %tensorflow_version only exists in Colab.\n",
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" %tensorflow_version 2.x\n",
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"except Exception:\n",
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" !pip install tensorflow-gpu>=2.0.0"
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]
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},
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{
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},
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"outputs": [],
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"source": [
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"!pip install --quiet tensorflow-gpu==2.0.0-rc0\n",
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"!pip install --quiet neural-structured-learning\n",
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"!pip install --quiet tensorflow-hub"
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]
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"timestamp": 1566436775546
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}
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],
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"toc_visible": true,
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"version": "0.3.2"
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"toc_visible": true
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},
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"kernelspec": {
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"display_name": "Python 3",

‎g3doc/tutorials/graph_keras_mlp_cora.ipynb

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"id": "pL9fF9FWI-Q1"
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},
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"source": [
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"<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://www.tensorflow.org/neural_structured_learning/tutorials/graph_keras_mlp_cora\"><img src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" />View on TensorFlow.org</a>\n",
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" </td>\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/graph_keras_mlp_cora.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
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" </td>\n",
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" <td>\n",
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" <a target=\"_blank\" href=\"https://github.com/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/graph_keras_mlp_cora.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
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" </td>\n",
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"</table>"
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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/neural_structured_learning/tutorials/graph_keras_mlp_cora\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/graph_keras_mlp_cora.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003eRun in Google Colab\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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" \u003ctd\u003e\n",
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" \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/neural-structured-learning/blob/master/g3doc/tutorials/graph_keras_mlp_cora.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
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" \u003c/td\u003e\n",
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"\u003c/table\u003e"
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]
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},
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{
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"id": "hgSLDi0SyBuO"
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},
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"source": [
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"1. Install TensorFlow 2.x to create an interactive developing environment with eager execution.\n",
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"1. Select TensorFlow 2.x to create an interactive development environment with eager execution.\n",
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"2. Install the Neural Structured Learning package."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 0,
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"metadata": {
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"colab": {},
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"colab_type": "code",
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"id": "gh6K6Onyy5bd"
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},
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"outputs": [],
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"source": [
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"try:\n",
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" # %tensorflow_version only exists in Colab.\n",
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" %tensorflow_version 2.x\n",
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"except Exception:\n",
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" !pip install tensorflow-gpu>=2.0.0"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 0,
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},
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"outputs": [],
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"source": [
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"!pip install --quiet tensorflow-gpu==2.0.0-rc0\n",
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"!pip install --quiet neural-structured-learning"
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]
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},
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"timestamp": 1560299386497
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}
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],
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"toc_visible": true,
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"version": "0.3.2"
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"toc_visible": true
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},
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"kernelspec": {
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"display_name": "Python 3",

‎neural_structured_learning/BUILD

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# Description:
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# Build rules for TensorFlow Neural Structured Learning.
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# Placeholder for internal Python strict compatibility macro.
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# Internal annotation for sync
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package(default_visibility = ["//visibility:public"])
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deps = [
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":version",
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"//neural_structured_learning/configs",
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"//neural_structured_learning/estimator",
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"//neural_structured_learning/keras",
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"//neural_structured_learning/lib",
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"//neural_structured_learning/tools",
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],
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)
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py_library(
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name = "version",
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srcs = ["version.py"],
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srcs_version = "PY2AND3",
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)

‎neural_structured_learning/__init__.py

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"""Subpackages of Neural Structured Learning."""
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from neural_structured_learning import configs
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from neural_structured_learning import estimator
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from neural_structured_learning import keras
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from neural_structured_learning import lib
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from neural_structured_learning import tools
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from neural_structured_learning.version import __version__

‎neural_structured_learning/configs/BUILD

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# Description:
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# Build rules for config libraries in Neural Structured Learning.
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# Placeholder for internal Python strict compatibility macro.
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package(
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default_visibility = ["//visibility:public"],
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licenses = ["notice"], # Apache 2.0

‎neural_structured_learning/estimator/BUILD

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# Copyright 2019 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Description:
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# Build rules for Estimator APIs in Neural Structured Learning.
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# Placeholder for internal Python strict compatibility macro.
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# Placeholder for internal Python version compatibility macro.
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package(
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default_visibility = ["//visibility:public"],
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licenses = ["notice"], # Apache 2.0
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)
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exports_files(["LICENSE"])
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py_library(
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name = "estimator",
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srcs = ["__init__.py"],
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srcs_version = "PY2AND3",
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deps = [
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":adversarial_regularization",
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":graph_regularization",
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],
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)
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py_library(
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name = "adversarial_regularization",
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srcs = ["adversarial_regularization.py"],
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srcs_version = "PY2AND3",
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deps = [
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"//neural_structured_learning/configs",
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"//neural_structured_learning/lib",
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# package tensorflow
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],
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)
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py_test(
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name = "adversarial_regularization_test",
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srcs = ["adversarial_regularization_test.py"],
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srcs_version = "PY2AND3",
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deps = [
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":estimator",
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"//neural_structured_learning/configs",
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# package numpy
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# package tensorflow
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# package tensorflow framework_test_lib,
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],
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)
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py_library(
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name = "graph_regularization",
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srcs = ["graph_regularization.py"],
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srcs_version = "PY2AND3",
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deps = [
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"//neural_structured_learning/configs",
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"//neural_structured_learning/lib:distances",
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"//neural_structured_learning/lib:utils",
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# package tensorflow
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],
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)
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py_test(
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name = "graph_regularization_test",
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srcs = ["graph_regularization_test.py"],
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srcs_version = "PY2AND3",
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deps = [
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":estimator",
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# package protobuf,
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"//neural_structured_learning/configs",
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# package numpy
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# package tensorflow
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# package tensorflow framework_test_lib,
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],
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)

‎neural_structured_learning/estimator/README.md

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# Estimator APIs for Neural Structured Learning.
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The implementations here are provided on a strict "as is" basis, without
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warranties or conditions of any kind. Also, these implementations may not be
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compatible with certain TensorFlow versions (such as 2.0 or above).

‎neural_structured_learning/estimator/__init__.py

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r"""Estimator APIs for Neural Structured Learning.
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The current NSL Estimator APIs may not be compatible with certain TensorFlow
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versions (such as 2.0 or above).
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"""
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from neural_structured_learning.estimator.adversarial_regularization import add_adversarial_regularization
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from neural_structured_learning.estimator.graph_regularization import add_graph_regularization
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__all__ = ['add_adversarial_regularization', 'add_graph_regularization']

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