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hmeine/compare_gan_model_fn_problem.ipynb

Created February 18, 2019 22:23
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compare_gan_model_fn_problem.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "compare_gan_model_fn_problem.ipynb",
"version": "0.3.2",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python2",
"display_name": "Python 2"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/hmeine/d7ef0c38790dc885f3f73e621e14ff31/compare_gan_model_fn_problem.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"metadata": {
"id": "kjX0lEWL1Sym",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1062
},
"outputId": "73495bfe-c433-4dd2-a6ff-ceb3e26d0ca1"
},
"cell_type": "code",
"source": [
"!pip install https://github.com/google/compare_gan/archive/master.zip"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": [
"Collecting https://github.com/google/compare_gan/archive/master.zip\n",
" Downloading https://github.com/google/compare_gan/archive/master.zip\n",
"\u001b[K \\ 1.6MB 93.9MB/s\n",
"Requirement already satisfied (use --upgrade to upgrade): compare-gan==1.0 from https://github.com/google/compare_gan/archive/master.zip in /usr/local/lib/python2.7/dist-packages\n",
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"Requirement already satisfied: greenlet>=0.4.14; platform_python_implementation == \"CPython\" in /usr/local/lib/python2.7/dist-packages (from gevent->tensor2tensor->compare-gan==1.0) (0.4.15)\n",
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"Requirement already satisfied: typing>=3.6.4; python_version < \"3.5\" in /usr/local/lib/python2.7/dist-packages (from promise->tfds-nightly->tensor2tensor->compare-gan==1.0) (3.6.6)\n",
"Requirement already satisfied: googleapis-common-protos in /usr/local/lib/python2.7/dist-packages (from tensorflow-metadata->tfds-nightly->tensor2tensor->compare-gan==1.0) (1.5.8)\n",
"Building wheels for collected packages: compare-gan\n",
" Building wheel for compare-gan (setup.py) ... \u001b[?25ldone\n",
"\u001b[?25h Stored in directory: /tmp/pip-ephem-wheel-cache-B70JSQ/wheels/c1/24/72/6f08cf0ceddc060aa540eb1495df2e08b9aca929adedcafefb\n",
"Successfully built compare-gan\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "Hzs7BZbu9-oK",
"colab_type": "code",
"outputId": "3760f815-d0ca-4cf6-ff2a-efa8c0950381",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 52
}
},
"cell_type": "code",
"source": [
"!pip install pstar"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"text": [
"Requirement already satisfied: pstar in /usr/local/lib/python2.7/dist-packages (0.1.6)\n",
"Requirement already satisfied: qj in /usr/local/lib/python2.7/dist-packages (from pstar) (0.1.5)\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "Qqsvhi743TBM",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"# hide jupyter commandline arguments from compare_gan\n",
"import sys\n",
"sys.argv = ['colab']"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "y_pRHBrT1sxJ",
"colab_type": "code",
"outputId": "3b6e8026-6ad6-4d26-eb9c-1775c5f433f5",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 139
}
},
"cell_type": "code",
"source": [
"from compare_gan.src import gan_lib"
],
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"text": [
"\n",
"WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
"For more information, please see:\n",
" * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
" * https://github.com/tensorflow/addons\n",
"If you depend on functionality not listed there, please file an issue.\n",
"\n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "UvUZBkVQ3UMo",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
"dataset = 'mnist'\n",
"dataset_content = gan_lib.load_dataset(dataset, split_name=\"train\")\n",
"dataset_content = dataset_content.repeat().shuffle(10000, seed=gan_lib.DEFAULT_DATASET_SEED)\n",
"\n",
"gan = gan_lib.create_gan(\n",
" gan_type='WGAN_GP',\n",
" dataset=dataset,\n",
" dataset_content=dataset_content,\n",
" options={u'architecture': u'infogan_arch',\n",
" u'batch_size': 64,\n",
" u'beta1': 0.5,\n",
" u'dataset': u'fake',\n",
" u'disc_iters': 5,\n",
" u'discriminator_normalization': u'none',\n",
" u'eval_test_samples': 50,\n",
" u'gan_type': u'WGAN_GP',\n",
" u'lambda': 10.0,\n",
" u'learning_rate': 9.999999747378752e-05,\n",
" u'save_checkpoint_steps': 10000,\n",
" u'tf_seed': 42,\n",
" u'training_steps': 100,\n",
" u'z_dim': 64},\n",
" gan_log_dir='log_dir',\n",
" result_dir='result_dir',\n",
" checkpoint_dir='checkpoint_dir')"
],
"execution_count": 0,
"outputs": []
},
{
"metadata": {
"id": "Rj6AIULXGeXa",
"colab_type": "code",
"outputId": "530a5c21-52ff-4232-d7bc-c8fc60a2724e",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 2303
}
},
"cell_type": "code",
"source": [
"import tensorflow as tf\n",
"gan.train_with_estimator(tf.contrib.tpu.RunConfig())"
],
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"text": [
"WARNING:tensorflow:Estimator's model_fn (<bound method WGAN_GP._model_fn of <compare_gan.src.gans.WGAN_GP.WGAN_GP object at 0x7f54031d8a90>>) includes params argument, but params are not passed to Estimator.\n",
"WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpxEzI8z\n",
"INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_session_config': allow_soft_placement: true\n",
"graph_options {\n",
" rewrite_options {\n",
" meta_optimizer_iterations: ONE\n",
" }\n",
"}\n",
", '_keep_checkpoint_max': 5, '_task_type': 'worker', '_train_distribute': None, '_is_chief': True, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f5403181890>, '_model_dir': '/tmp/tmpxEzI8z', '_protocol': None, '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_service': None, '_num_ps_replicas': 0, '_tpu_config': TPUConfig(iterations_per_loop=2, num_shards=None, num_cores_per_replica=None, per_host_input_for_training=2, tpu_job_name=None, initial_infeed_sleep_secs=None, input_partition_dims=None), '_tf_random_seed': None, '_save_summary_steps': 100, '_device_fn': None, '_cluster': None, '_experimental_distribute': None, '_num_worker_replicas': 1, '_task_id': 0, '_log_step_count_steps': None, '_evaluation_master': '', '_eval_distribute': None, '_global_id_in_cluster': 0, '_master': ''}\n",
"INFO:tensorflow:_TPUContext: eval_on_tpu True\n",
"WARNING:tensorflow:eval_on_tpu ignored because use_tpu is False.\n",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/resource_variable_ops.py:435: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Colocations handled automatically by placer.\n",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/compare_gan/src/gans/abstract_gan.py:334: make_one_shot_iterator (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Use `for ... in dataset:` to iterate over a dataset. If using `tf.estimator`, return the `Dataset` object directly from your input function. As a last resort, you can use `tf.compat.v1.data.make_one_shot_iterator(dataset)`.\n",
"WARNING:tensorflow:The graph (<tensorflow.python.framework.ops.Graph object at 0x7f5468c89d10>) of the iterator is different from the graph (<tensorflow.python.framework.ops.Graph object at 0x7f54035a8550>) the dataset: <DatasetV1Adapter shapes: ((?, ?, ?), ()), types: (tf.float32, tf.int32)> was created in. If you are using the Estimator API, make sure that no part of the dataset returned by the `input_fn` function is defined outside the `input_fn` function.Please ensure that all datasets in the pipeline are created in the same graph as the iterator. NOTE: This warning will become an error in future versions of TensorFlow.\n",
"WARNING:tensorflow:The graph (<tensorflow.python.framework.ops.Graph object at 0x7f5468c89d10>) of the iterator is different from the graph (<tensorflow.python.framework.ops.Graph object at 0x7f54035a8550>) the dataset: <DatasetV1Adapter shapes: ((?, ?, ?), ()), types: (tf.float32, tf.int32)> was created in. If you are using the Estimator API, make sure that no part of the dataset returned by the `input_fn` function is defined outside the `input_fn` function.Please ensure that all datasets in the pipeline are created in the same graph as the iterator. NOTE: This warning will become an error in future versions of TensorFlow.\n",
"WARNING:tensorflow:The graph (<tensorflow.python.framework.ops.Graph object at 0x7f5468c89d10>) of the iterator is different from the graph (<tensorflow.python.framework.ops.Graph object at 0x7f54035a8550>) the dataset: <DatasetV1Adapter shapes: ((?, ?, ?), ()), types: (tf.float32, tf.int32)> was created in. If you are using the Estimator API, make sure that no part of the dataset returned by the `input_fn` function is defined outside the `input_fn` function.Please ensure that all datasets in the pipeline are created in the same graph as the iterator. NOTE: This warning will become an error in future versions of TensorFlow.\n",
"WARNING:tensorflow:The graph (<tensorflow.python.framework.ops.Graph object at 0x7f5468c89d10>) of the iterator is different from the graph (<tensorflow.python.framework.ops.Graph object at 0x7f54035a8550>) the dataset: <TFRecordDatasetV1 shapes: (), types: tf.string> was created in. If you are using the Estimator API, make sure that no part of the dataset returned by the `input_fn` function is defined outside the `input_fn` function.Please ensure that all datasets in the pipeline are created in the same graph as the iterator. NOTE: This warning will become an error in future versions of TensorFlow.\n",
"WARNING:tensorflow:The graph (<tensorflow.python.framework.ops.Graph object at 0x7f5468c89d10>) of the iterator is different from the graph (<tensorflow.python.framework.ops.Graph object at 0x7f54035a8550>) the dataset: <TensorSliceDataset shapes: (), types: tf.string> was created in. If you are using the Estimator API, make sure that no part of the dataset returned by the `input_fn` function is defined outside the `input_fn` function.Please ensure that all datasets in the pipeline are created in the same graph as the iterator. NOTE: This warning will become an error in future versions of TensorFlow.\n",
"WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/compare_gan/src/gans/abstract_gan.py:338: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Use tf.cast instead.\n",
"INFO:tensorflow:Calling model_fn.\n",
"INFO:tensorflow:Running train on CPU\n",
"INFO:tensorflow:Error recorded from training_loop: _model_fn() must be implemented in subclasses of AbstractGAN.\n",
"INFO:tensorflow:training_loop marked as finished\n",
"WARNING:tensorflow:Reraising captured error\n"
],
"name": "stdout"
},
{
"output_type": "error",
"ename": "NotImplementedError",
"evalue": "ignored",
"traceback": [
"\u001b[0;31m\u001b[0m",
"\u001b[0;31mNotImplementedError\u001b[0mTraceback (most recent call last)",
"\u001b[0;32m<ipython-input-8-b6e6886d6953>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtensorflow\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mgan\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain_with_estimator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtpu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRunConfig\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/compare_gan/src/gans/abstract_gan.pyc\u001b[0m in \u001b[0;36mtrain_with_estimator\u001b[0;34m(self, config, warm_start_from)\u001b[0m\n\u001b[1;32m 396\u001b[0m \u001b[0meval_batch_size\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 397\u001b[0m warm_start_from=warm_start_from)\n\u001b[0;32m--> 398\u001b[0;31m \u001b[0mestimator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_fn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_input_fn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax_steps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraining_steps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 399\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 400\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msess\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprogress_reporter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.pyc\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, input_fn, hooks, steps, max_steps, saving_listeners)\u001b[0m\n\u001b[1;32m 2455\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2456\u001b[0m \u001b[0mrendezvous\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecord_done\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'training_loop'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2457\u001b[0;31m \u001b[0mrendezvous\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2458\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2459\u001b[0m def evaluate(self,\n",
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"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.pyc\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, input_fn, hooks, steps, max_steps, saving_listeners)\u001b[0m\n\u001b[1;32m 2450\u001b[0m \u001b[0msteps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2451\u001b[0m \u001b[0mmax_steps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmax_steps\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2452\u001b[0;31m saving_listeners=saving_listeners)\n\u001b[0m\u001b[1;32m 2453\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;31m# pylint: disable=broad-except\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2454\u001b[0m \u001b[0mrendezvous\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecord_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'training_loop'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexc_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/estimator.pyc\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, input_fn, hooks, steps, max_steps, saving_listeners)\u001b[0m\n\u001b[1;32m 356\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 357\u001b[0m \u001b[0msaving_listeners\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_check_listeners_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msaving_listeners\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 358\u001b[0;31m \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_train_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_fn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhooks\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msaving_listeners\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 359\u001b[0m \u001b[0mlogging\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Loss for final step: %s.'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 360\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/estimator.pyc\u001b[0m in \u001b[0;36m_train_model_default\u001b[0;34m(self, input_fn, hooks, saving_listeners)\u001b[0m\n\u001b[1;32m 1152\u001b[0m \u001b[0mworker_hooks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_hooks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1153\u001b[0m estimator_spec = self._call_model_fn(\n\u001b[0;32m-> 1154\u001b[0;31m features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)\n\u001b[0m\u001b[1;32m 1155\u001b[0m \u001b[0mglobal_step_tensor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtraining_util\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_global_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1156\u001b[0m return self._train_with_estimator_spec(estimator_spec, worker_hooks,\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.pyc\u001b[0m in \u001b[0;36m_call_model_fn\u001b[0;34m(self, features, labels, mode, config)\u001b[0m\n\u001b[1;32m 2249\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2250\u001b[0m return super(TPUEstimator, self)._call_model_fn(features, labels, mode,\n\u001b[0;32m-> 2251\u001b[0;31m config)\n\u001b[0m\u001b[1;32m 2252\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2253\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_call_model_fn_for_inference\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow_estimator/python/estimator/estimator.pyc\u001b[0m in \u001b[0;36m_call_model_fn\u001b[0;34m(self, features, labels, mode, config)\u001b[0m\n\u001b[1;32m 1110\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1111\u001b[0m \u001b[0mlogging\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Calling model_fn.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1112\u001b[0;31m \u001b[0mmodel_fn_results\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_model_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1113\u001b[0m \u001b[0mlogging\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Done calling model_fn.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1114\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.pyc\u001b[0m in \u001b[0;36m_model_fn\u001b[0;34m(features, labels, mode, config, params)\u001b[0m\n\u001b[1;32m 2532\u001b[0m \u001b[0mlogging\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minfo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Running %s on CPU'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2533\u001b[0m estimator_spec = model_fn_wrapper.call_without_tpu(\n\u001b[0;32m-> 2534\u001b[0;31m features, labels, is_export_mode=is_export_mode)\n\u001b[0m\u001b[1;32m 2535\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_log_every_n_steps\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2536\u001b[0m estimator_spec = estimator_spec._replace(\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.pyc\u001b[0m in \u001b[0;36mcall_without_tpu\u001b[0;34m(self, features, labels, is_export_mode)\u001b[0m\n\u001b[1;32m 1321\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1322\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcall_without_tpu\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_export_mode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1323\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_call_model_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_export_mode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mis_export_mode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1324\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1325\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mconvert_to_single_tpu_train_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdequeue_fn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.pyc\u001b[0m in \u001b[0;36m_call_model_fn\u001b[0;34m(self, features, labels, is_export_mode)\u001b[0m\n\u001b[1;32m 1591\u001b[0m \u001b[0m_add_item_to_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_CTX_KEY\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0muser_context\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1592\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1593\u001b[0;31m \u001b[0mestimator_spec\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_model_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1594\u001b[0m if (running_on_cpu and\n\u001b[1;32m 1595\u001b[0m isinstance(estimator_spec, model_fn_lib._TPUEstimatorSpec)): # pylint: disable=protected-access\n",
"\u001b[0;32m/usr/local/lib/python2.7/dist-packages/compare_gan/src/gans/abstract_gan.pyc\u001b[0m in \u001b[0;36m_model_fn\u001b[0;34m(self, features, labels, mode, params)\u001b[0m\n\u001b[1;32m 372\u001b[0m \"\"\"\n\u001b[1;32m 373\u001b[0m raise NotImplementedError(\n\u001b[0;32m--> 374\u001b[0;31m \"_model_fn() must be implemented in subclasses of AbstractGAN.\")\n\u001b[0m\u001b[1;32m 375\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 376\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mtrain_with_estimator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwarm_start_from\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNotImplementedError\u001b[0m: _model_fn() must be implemented in subclasses of AbstractGAN."
]
}
]
},
{
"metadata": {
"id": "vUKjzH2PqoxF",
"colab_type": "code",
"outputId": "e9501f58-e65d-49c9-99d3-303acfae9ee1",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 173
}
},
"cell_type": "code",
"source": [
"!pip list | grep tensor"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"mesh-tensorflow 0.0.5 \n",
"tensor2tensor 1.11.0 \n",
"tensorboard 1.12.2 \n",
"tensorboardcolab 0.0.22 \n",
"tensorflow 1.13.0rc1 \n",
"tensorflow-estimator 1.13.0rc0 \n",
"tensorflow-hub 0.2.0 \n",
"tensorflow-metadata 0.9.0 \n",
"tensorflow-probability 0.5.0 \n"
],
"name": "stdout"
}
]
},
{
"metadata": {
"id": "FA0suxxiqpgV",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
""
],
"execution_count": 0,
"outputs": []
}
]
}
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