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Update eval frequency param from 'min_eval_frequency' to 'throttle_secs' for TensorFlow 1.6
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sagemaker-python-sdk/tensorflow_resnet_cifar10_with_tensorboard/tensorflow_resnet_cifar10_with_tensorboard.ipynb

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@@ -51,6 +51,7 @@
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"scrolled": false
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},
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"outputs": [],
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"scrolled": false
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},
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"outputs": [],
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"estimator = TensorFlow(entry_point='resnet_cifar_10.py',\n",
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" source_dir=source_dir,\n",
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" role=role,\n",
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" hyperparameters={'min_eval_frequency': 10},\n",
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" hyperparameters={'throttle_secs': 30},\n",
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" training_steps=1000, evaluation_steps=100,\n",
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" train_instance_count=2, train_instance_type='ml.c4.xlarge', \n",
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" base_job_name='tensorboard-example')\n",
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"\n",
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"It takes a few minutes to provision containers and start the training job.**TensorBoard** will start to display metrics shortly after that.\n",
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"\n",
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"You can access **TensorBoard** locally at [http://localhost:6006](http://localhost:6006) or using your SageMaker notebook instance [proxy/6006/](/proxy/6006/)(TensorBoard will not work if forget to put the slash, '/', in end of the url). If TensorBoard started on a different port, adjust these URLs to match.",
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"This example uses the optional hyperparameter **```min_eval_frequency```** to generate training evaluations more often, allowing to visualize **TensorBoard** scalar data faster. You can find the available optional hyperparameters [here](https://github.com/aws/sagemaker-python-sdk#optional-hyperparameters)**."
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"You can access **TensorBoard** locally at [http://localhost:6006](http://localhost:6006) or using your SageMaker notebook instance [proxy/6006/](/proxy/6006/)(TensorBoard will not work if forget to put the slash, '/', in end of the url). If TensorBoard started on a different port, adjust these URLs to match.This example uses the optional hyperparameter **```throttle_secs```** to generate training evaluations more often, allowing to visualize **TensorBoard** scalar data faster. You can find the available optional hyperparameters [here](https://github.com/aws/sagemaker-python-sdk#optional-hyperparameters)."
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]
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},
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{
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}
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],
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"metadata": {
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"notice": "Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the \"License\"). You may not use this file except in compliance with the License. A copy of the License is located at http://aws.amazon.com/apache2.0/ or in the \"license\" file accompanying this file. This file is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.",
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"kernelspec": {
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"display_name": "Environment (conda_tensorflow_p27)",
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"display_name": "conda_tensorflow_p27",
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"language": "python",
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"name": "conda_tensorflow_p27"
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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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"version": 2
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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": "2.7.13"
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}
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"pygments_lexer": "ipython2",
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"version": "2.7.11"
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},
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"notice": "Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the \"License\"). You may not use this file except in compliance with the License. A copy of the License is located at http://aws.amazon.com/apache2.0/ or in the \"license\" file accompanying this file. This file is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
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},
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"nbformat": 4,
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"nbformat_minor": 2

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