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

Author: yangaws

CHANGELOG.rst

@@ -2,6 +2,11 @@
 CHANGELOG
 =========
 
+1.10.0
+======
+
+* feature: add support for TensorFlow 1.10.0
+
 1.9.3.1
 =======
 

README.rst

@@ -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.
 

setup.py

@@ -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'},

src/sagemaker/tensorflow/README.rst

@@ -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
 ~~~~~~~~~~~~~~~~~~~~~~~~

src/sagemaker/tensorflow/defaults.py

@@ -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'

tests/conftest.py

@@ -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