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Add support for tensorflow 1.10.0 and bump version up to 1.9.4 #385

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Sep 6, 2018
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Add support for tensorflow 1.10.0 and bump version up to 1.9.4 #385

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5 changes: 5 additions & 0 deletions CHANGELOG.rst
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Expand Up @@ -2,6 +2,11 @@
CHANGELOG
=========

1.10.0
======

* feature: add support for TensorFlow 1.10.0

1.9.3.1
=======

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2 changes: 1 addition & 1 deletion README.rst
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Expand Up @@ -256,7 +256,7 @@ TensorFlow SageMaker Estimators

By using TensorFlow SageMaker ``Estimators``, you can train and host TensorFlow models on Amazon SageMaker.

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

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 setup.py
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Expand Up @@ -23,7 +23,7 @@ def read(fname):


setup(name="sagemaker",
version="1.9.3.1",
version="1.9.4",
description="Open source library for training and deploying models on Amazon SageMaker.",
packages=find_packages('src'),
package_dir={'': 'src'},
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2 changes: 1 addition & 1 deletion src/sagemaker/tensorflow/README.rst
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Expand Up @@ -6,7 +6,7 @@ TensorFlow SageMaker Estimators allow you to run your own TensorFlow
training algorithms on SageMaker Learner, and to host your own TensorFlow
models on SageMaker Hosting.

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

Training with TensorFlow
~~~~~~~~~~~~~~~~~~~~~~~~
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2 changes: 1 addition & 1 deletion src/sagemaker/tensorflow/defaults.py
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Expand Up @@ -12,4 +12,4 @@
# language governing permissions and limitations under the License.
from __future__ import absolute_import

TF_VERSION = '1.9'
TF_VERSION = '1.10'
3 changes: 2 additions & 1 deletion tests/conftest.py
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Expand Up @@ -80,7 +80,8 @@ def sagemaker_local_session(boto_config):


@pytest.fixture(scope='module', params=['1.4', '1.4.1', '1.5', '1.5.0', '1.6', '1.6.0',
'1.7', '1.7.0', '1.8', '1.8.0', '1.9', '1.9.0'])
'1.7', '1.7.0', '1.8', '1.8.0', '1.9', '1.9.0',
'1.10', '1.10.0'])
def tf_version(request):
return request.param

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