From 7b1fa5fc47f32a72e638937cdb19e6947d7df452 Mon Sep 17 00:00:00 2001 From: Nicholas Connor Date: Tue, 16 Jan 2018 13:27:50 -0500 Subject: [PATCH] Update TensorFlow examples following API change It appears at some point the function definition for TensorFlow was changed and any code using these previous examples will break (the SageMaker environment appears to auto-update.. so assumably that code "is broken"). The current function signature def is ` def __init__(self, training_steps=None, evaluation_steps=None, checkpoint_path=None, py_version="py2", **kwargs):` --- README.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.rst b/README.rst index 1bb4d00679..6967fa376b 100644 --- a/README.rst +++ b/README.rst @@ -717,7 +717,7 @@ follows: from sagemaker.tensorflow import TensorFlow - tf_estimator = TensorFlow('tf-train.py', role='SageMakerRole', + tf_estimator = TensorFlow(entry_point='tf-train.py', role='SageMakerRole', training_steps=10000, evaluation_steps=100, train_instance_count=1, train_instance_type='ml.p2.xlarge') tf_estimator.fit('s3://bucket/path/to/training/data') @@ -1041,7 +1041,7 @@ The following code sample shows how to train a custom TensorFlow script 'tf-trai from sagemaker.tensorflow import TensorFlow - tf_estimator = TensorFlow('tf-train.py', role='SageMakerRole', + tf_estimator = TensorFlow(entry_point='tf-train.py', role='SageMakerRole', training_steps=10000, evaluation_steps=100, train_instance_count=1, train_instance_type='ml.p2.xlarge') tf_estimator.fit('s3://bucket/path/to/training/data')