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Fixes for mvs #81

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Merged
merged 5 commits into from
Nov 27, 2017
Merged

Fixes for mvs #81

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e3c4e2c
Update tensorflow_resnet_cifar10_with_tensorboard.ipynb
Nov 27, 2017
7c104f6
Update tensorflow_abalone_age_predictor_using_layers.ipynb
Nov 27, 2017
e427975
Need to demonstrate prediction
Nov 27, 2017
172b5b8
Update tensorflow_abalone_age_predictor_using_layers.ipynb
mvsusp Nov 27, 2017
f07f445
fix
Nov 27, 2017
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12 changes: 6 additions & 6 deletions ...ow_abalone_age_predictor_using_layers/tensorflow_abalone_age_predictor_using_layers.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -95,7 +95,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"**sagemaker_session.upload_data** will upload the abalone dataset from your machine to a bucket named **sagemaker-{your aws account number}**, if you don't have this bucket yet, sagemaker_session will create it for you."
"**sagemaker_session.upload_data** will upload the abalone dataset from your machine to a bucket named **sagemaker-{region}-{your aws account number}**, if you don't have this bucket yet, sagemaker_session will create it for you."
]
},
{
Expand Down Expand Up @@ -136,7 +136,7 @@
" return EstimatorSpec(mode, predictions, loss, train_op, eval_metric_ops)\n",
"```\n",
"\n",
"The **`model_fn`** must accept three arguments:\n",
"The **`model_fn`** requires three arguments:\n",
"\n",
"* **`features`**: A dict containing the features passed to the model via\n",
" **`input_fn`**.\n",
Expand All @@ -149,7 +149,7 @@
" mode, namely via a `train()` call.\n",
" * **`EVAL`** The **`model_fn`** was invoked in\n",
" evaluation mode, namely via an `evaluate()` call.\n",
" * **`PREDICT`** The `model_fn` was invoked in\n",
" * **`PREDICT`** The **`model_fn`** was invoked in\n",
" predict mode, namely via a `predict()` call.\n",
"\n",
"**`model_fn`** may also accept a **`hyperparameters`** argument containing a dict of\n",
Expand Down Expand Up @@ -270,7 +270,7 @@
" inputs=input_layer, units=10, activation=tf.nn.relu)\n",
" ```\n",
"\n",
"* **`tf.nn.relu6`**. The following code creates a layer of `units` nodes fully\n",
"* **`tf.nn.relu`**. The following code creates a layer of `units` nodes fully\n",
" connected to the previous layer `hidden_layer` with a ReLU activation\n",
" function:\n",
"\n",
Expand Down Expand Up @@ -531,7 +531,7 @@
"* deploy your script in a container with tensorflow installed\n",
"* copy the data from the bucket to the container\n",
"* instantiate the tf.estimator\n",
"* train the estimator with 10 training steps\n",
"* train the estimator with 100 training steps\n",
"* save the estimator model"
]
},
Expand Down Expand Up @@ -637,4 +637,4 @@
},
"nbformat": 4,
"nbformat_minor": 2
}
}
11 changes: 9 additions & 2 deletions ...nsorflow_resnet_cifar10_with_tensorboard/tensorflow_resnet_cifar10_with_tensorboard.ipynb
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Expand Up @@ -32,7 +32,6 @@
"source": [
"import os\n",
"import sagemaker\n",
"import tensorflow\n",
"from sagemaker import get_execution_role\n",
"\n",
"sagemaker_session = sagemaker.Session()\n",
Expand Down Expand Up @@ -83,7 +82,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"**sagemaker_session.upload_data** will upload the CIFAR-10 dataset from your machine to a bucket named **sagemaker-{*your aws account number*}**, if you don't have this bucket yet, sagemaker_session will create it for you."
"**sagemaker_session.upload_data** will upload the CIFAR-10 dataset from your machine to a bucket named **sagemaker-{region}-{*your aws account number*}**, if you don't have this bucket yet, sagemaker_session will create it for you."
]
},
{
Expand Down Expand Up @@ -163,6 +162,14 @@
"predictor = estimator.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Prediction using the trained model\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down