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yuanzhuayuanzhua
authoredMar 6, 2020
upgrade framework version (aws#1079)
·
v0.1.0
1 parent f065b92 commit 55dd33e

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18 files changed

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-29
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18 files changed

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-29
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‎sagemaker-python-sdk/managed_spot_training_mxnet/managed_spot_training_mxnet.ipynb

+1-1
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@@ -102,7 +102,7 @@
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" code_location=custom_code_upload_location,\n",
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" train_instance_count=1,\n",
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" train_instance_type='ml.m4.xlarge',\n",
105-
" framework_version='1.4.1',\n",
105+
" framework_version='1.6.0',\n",
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" py_version='py3',\n",
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" distributions={'parameter_server': {'enabled': True}},\n",
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" hyperparameters={'learning-rate': 0.1},\n",

‎sagemaker-python-sdk/mxnet_gluon_embedding_server/mxnet_embedding_server.ipynb

+1-1
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@@ -344,7 +344,7 @@
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" role=get_execution_role(),\n",
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" py_version='py3',\n",
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" entry_point='embedding_server.py',\n",
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" framework_version='1.4',\n",
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" framework_version='1.6.0',\n",
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" env={'modelname': modelname}) # we pass model name via an environment variable"
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]
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},

‎sagemaker-python-sdk/mxnet_gluon_mnist/mxnet_mnist_with_gluon.ipynb

+1-1
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@@ -102,7 +102,7 @@
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" role=role,\n",
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" train_instance_count=1,\n",
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" train_instance_type=\"ml.c4.xlarge\",\n",
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" framework_version=\"1.4.1\",\n",
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" framework_version=\"1.6.0\",\n",
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" py_version=\"py3\",\n",
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" hyperparameters={'batch-size': 100,\n",
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" 'epochs': 20,\n",

‎sagemaker-python-sdk/mxnet_gluon_mnist/mxnet_mnist_with_gluon_local_mode.ipynb

+1-1
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@@ -134,7 +134,7 @@
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" role=role,\n",
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" train_instance_count=1,\n",
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" train_instance_type=instance_type,\n",
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" framework_version=\"1.4.1\",\n",
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" framework_version=\"1.6.0\",\n",
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" py_version=\"py3\",\n",
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" hyperparameters={'batch-size': 100,\n",
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" 'epochs': 20,\n",

‎sagemaker-python-sdk/mxnet_gluon_sentiment/mxnet_sentiment_analysis_with_gluon.ipynb

+1-1
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@@ -111,7 +111,7 @@
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" role=role,\n",
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" train_instance_count=1,\n",
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" train_instance_type='ml.c4.xlarge',\n",
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" framework_version='1.4.1',\n",
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" framework_version='1.6.0',\n",
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" py_version='py3',\n",
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" distributions={'parameter_server': {'enabled': True}},\n",
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" hyperparameters={'batch-size': 8,\n",

‎sagemaker-python-sdk/mxnet_mnist/mxnet_mnist_with_batch_transform.ipynb

+1-1
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@@ -92,7 +92,7 @@
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" code_location=custom_code_upload_location,\n",
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" train_instance_count=1,\n",
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" train_instance_type='ml.m4.xlarge',\n",
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" framework_version='1.4.1',\n",
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" framework_version='1.6.0',\n",
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" py_version='py3',\n",
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" hyperparameters={'learning-rate': 0.1})"
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]

‎sagemaker-python-sdk/mxnet_onnx_export/mxnet_onnx_export.ipynb

+1-1
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@@ -128,7 +128,7 @@
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" code_location=custom_code_upload_location,\n",
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" train_instance_count=1,\n",
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" train_instance_type='ml.m4.xlarge',\n",
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" framework_version='1.4.1',\n",
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" framework_version='1.6.0',\n",
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" py_version='py3',\n",
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" hyperparameters={'learning-rate': 0.1})\n",
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"\n",

‎sagemaker-python-sdk/mxnet_onnx_superresolution/mxnet_onnx.ipynb

+1-1
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@@ -140,7 +140,7 @@
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" entry_point='super_resolution.py',\n",
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" role=role,\n",
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" py_version='py3',\n",
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" framework_version='1.3.0')"
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" framework_version='1.6.0')"
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]
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},
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{

‎sagemaker-python-sdk/pytorch_cnn_cifar10/pytorch_local_mode_cifar10.ipynb

+1-1
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@@ -196,7 +196,7 @@
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"\n",
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"cifar10_estimator = PyTorch(entry_point='source/cifar10.py',\n",
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" role=role,\n",
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" framework_version='1.2.0',\n",
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" framework_version='1.4.0',\n",
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" train_instance_count=1,\n",
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" train_instance_type=instance_type)\n",
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"\n",

‎sagemaker-python-sdk/pytorch_horovod_mnist/pytorch_mnist_horovod.ipynb

+1-1
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@@ -158,7 +158,7 @@
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"estimator = PyTorch(entry_point='mnist.py',\n",
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" source_dir='code',\n",
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" role=role,\n",
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" framework_version='1.3.1',\n",
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" framework_version='1.4.0',\n",
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" train_instance_count=2,\n",
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" train_instance_type='ml.p2.xlarge',\n",
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" hyperparameters={\n",

‎sagemaker-python-sdk/pytorch_lstm_word_language_model/pytorch_rnn.ipynb

+1-1
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@@ -193,7 +193,7 @@
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"\n",
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"estimator = PyTorch(entry_point='train.py',\n",
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" role=role,\n",
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" framework_version='1.2.0',\n",
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" framework_version='1.4.0',\n",
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" train_instance_count=1,\n",
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" train_instance_type='ml.p2.xlarge',\n",
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" source_dir='pytorch-rnn-scripts',\n",

‎sagemaker-python-sdk/pytorch_mnist/pytorch_mnist.ipynb

+1-1
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@@ -156,7 +156,7 @@
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"\n",
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"estimator = PyTorch(entry_point='mnist.py',\n",
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" role=role,\n",
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" framework_version='1.2.0',\n",
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" framework_version='1.4.0',\n",
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" train_instance_count=2,\n",
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" train_instance_type='ml.c4.xlarge',\n",
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" hyperparameters={\n",

‎sagemaker-python-sdk/tensorflow_moving_from_framework_mode_to_script_mode/tensorflow_moving_from_framework_mode_to_script_mode.ipynb

+1-1
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@@ -178,7 +178,7 @@
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"mnist_estimator = TensorFlow(entry_point='train.py',\n",
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" dependencies=['mnist.py'],\n",
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" role=role,\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" hyperparameters={'training_steps':10, 'evaluation_steps':10},\n",
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" py_version='py3',\n",
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" train_instance_count=1,\n",

‎sagemaker-python-sdk/tensorflow_script_mode_horovod/tensorflow_script_mode_horovod.ipynb

+4-4
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@@ -259,7 +259,7 @@
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" train_instance_count=instance_count,\n",
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" train_instance_type=train_instance_type,\n",
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" script_mode=True,\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" py_version='py3',\n",
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" distributions=distributions,\n",
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" base_job_name='hvd-mnist-local')"
@@ -335,7 +335,7 @@
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" train_instance_count=instance_count,\n",
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" train_instance_type=train_instance_type,\n",
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" script_mode=True,\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" py_version='py3',\n",
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" distributions=distributions,\n",
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" base_job_name='hvd-mnist')"
@@ -398,7 +398,7 @@
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" train_instance_count=instance_count,\n",
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" train_instance_type=train_instance_type,\n",
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" script_mode=True,\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" py_version='py3',\n",
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" distributions=distributions,\n",
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" base_job_name='hvd-mnist-multi-cpu')"
@@ -519,7 +519,7 @@
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" train_instance_count=instance_count,\n",
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" train_instance_type=train_instance_type,\n",
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" script_mode=True,\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" py_version='py3',\n",
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" distributions=distributions,\n",
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" security_group_ids=security_groups,\n",

‎sagemaker-python-sdk/tensorflow_script_mode_pipe_mode/tensorflow_script_mode_pipe_mode.ipynb

+1-1
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@@ -127,7 +127,7 @@
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"\n",
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"tensorflow = TensorFlow(entry_point='pipemode.py',\n",
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" role=role,\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" input_mode='Pipe',\n",
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" output_path=model_artifacts_location,\n",
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" code_location=custom_code_upload_location,\n",

‎sagemaker-python-sdk/tensorflow_script_mode_quickstart/tensorflow_script_mode_quickstart.ipynb

+2-2
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@@ -200,7 +200,7 @@
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" train_instance_count=1,\n",
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" hyperparameters=hyperparameters,\n",
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" role=sagemaker.get_execution_role(), # Passes to the container the AWS role that you are using on this notebook\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" py_version='py3',\n",
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" script_mode=True)"
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]
@@ -319,7 +319,7 @@
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" train_instance_count=1,\n",
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" hyperparameters=hyperparameters,\n",
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" role=sagemaker.get_execution_role(),\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" py_version='py3',\n",
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" script_mode=True)\n",
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" \n",

‎sagemaker-python-sdk/tensorflow_script_mode_training_and_serving/tensorflow_script_mode_training_and_serving.ipynb

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@@ -81,7 +81,7 @@
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"source": [
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"!pygmentize 'mnist.py'\n",
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"\n",
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"# TensorFlow 2.0 script\n",
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"# TensorFlow 2.1 script\n",
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"!pygmentize 'mnist-2.py'"
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]
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},
@@ -114,7 +114,7 @@
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" role=role,\n",
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" train_instance_count=2,\n",
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" train_instance_type='ml.p2.xlarge',\n",
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" framework_version='1.14',\n",
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" framework_version='1.15.2',\n",
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" py_version='py3',\n",
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" distributions={'parameter_server': {'enabled': True}})"
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]
@@ -123,7 +123,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can also initiate an estimator to train with TensorFlow 2.0 script. The only things that you will need to change are the script name and ``framewotk_version``"
126+
"You can also initiate an estimator to train with TensorFlow 2.1 script. The only things that you will need to change are the script name and ``framewotk_version``"
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]
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},
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{
@@ -138,7 +138,7 @@
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" role=role,\n",
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" train_instance_count=2,\n",
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" train_instance_type='ml.p2.xlarge',\n",
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" framework_version='2.0.0',\n",
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" framework_version='2.1.0',\n",
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" py_version='py3',\n",
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" distributions={'parameter_server': {'enabled': True}})"
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]
@@ -175,7 +175,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Calling fit to train a model with TensorFlow 2.0 scroipt."
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"Calling fit to train a model with TensorFlow 2.1 scroipt."
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]
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},
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{
@@ -215,7 +215,7 @@
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"collapsed": true
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},
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"source": [
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"Deployed the trained TensorFlow 2.0 model to an endpoint."
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"Deployed the trained TensorFlow 2.1 model to an endpoint."
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]
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},
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{
@@ -277,7 +277,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Examine the prediction result from the TensorFlow 2.0 model."
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"Examine the prediction result from the TensorFlow 2.1 model."
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]
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},
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{
@@ -315,7 +315,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Delete the TensorFlow 2.0 endpoint as well."
318+
"Delete the TensorFlow 2.1 endpoint as well."
319319
]
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},
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{

‎sagemaker-python-sdk/tensorflow_serving_container/tensorflow_serving_container.ipynb

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191191
"# predictable model.\n",
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"env = {'SAGEMAKER_TFS_DEFAULT_MODEL_NAME': 'mobilenet_v2_140_224'}\n",
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"\n",
194-
"model = Model(model_data=model_data, role=sagemaker_role, framework_version='1.14', env=env)\n",
194+
"model = Model(model_data=model_data, role=sagemaker_role, framework_version='1.15.2', env=env)\n",
195195
"predictor = model.deploy(initial_instance_count=1, instance_type='ml.c5.xlarge')"
196196
]
197197
},

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