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update EI version for TF to 1.12 #597

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Merged
merged 3 commits into from
Jan 15, 2019
Merged

update EI version for TF to 1.12 #597

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edad291
update EI version for TF to 1.12
Jan 11, 2019
f77fc36
update changelog
Jan 11, 2019
2cd5ecf
Merge branch 'master' into ei_tf_1.12
ChoiByungWook Jan 12, 2019
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5 changes: 5 additions & 0 deletions CHANGELOG.rst
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Expand Up @@ -2,6 +2,11 @@
CHANGELOG
=========

1.17.3.dev
==========

* feature: Update EI TensorFlow latest version to 1.12

1.17.2
======

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2 changes: 1 addition & 1 deletion README.rst
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Expand Up @@ -390,7 +390,7 @@ By using TensorFlow SageMaker ``Estimators``, you can train and host TensorFlow

Supported versions of TensorFlow: ``1.4.1``, ``1.5.0``, ``1.6.0``, ``1.7.0``, ``1.8.0``, ``1.9.0``, ``1.10.0``, ``1.11.0``, ``1.12.0``.

Supported versions of TensorFlow for Elastic Inference: ``1.11.0``.
Supported versions of TensorFlow for Elastic Inference: ``1.11.0``, ``1.12.0``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

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2 changes: 1 addition & 1 deletion src/sagemaker/tensorflow/README.rst
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Expand Up @@ -20,7 +20,7 @@ Documentation of the previous Legacy Mode versions: `1.4.1 <https://github.com/a
| You can find the Legacy Mode README `here <https://github.com/aws/sagemaker-python-sdk/tree/v1.12.0/src/sagemaker/tensorflow#tensorflow-sagemaker-estimators-and-models>`_. |
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

Supported versions of TensorFlow for Elastic Inference: ``1.11.0``.
Supported versions of TensorFlow for Elastic Inference: ``1.11.0``, ``1.12.0``.

Training with TensorFlow
~~~~~~~~~~~~~~~~~~~~~~~~
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2 changes: 1 addition & 1 deletion tests/conftest.py
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Expand Up @@ -131,7 +131,7 @@ def tf_version(request):
return request.param


@pytest.fixture(scope='module', params=['1.11', '1.11.0'])
@pytest.fixture(scope='module', params=['1.12', '1.12.0'])
def ei_tf_version(request):
return request.param

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