Create regional S3 client for model exporting

src/tf_container/experiment_trainer.py

@@ -1,27 +1,26 @@
 #  Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
-#  
+#
 #  Licensed under the Apache License, Version 2.0 (the "License").
 #  You may not use this file except in compliance with the License.
 #  A copy of the License is located at
-#  
+#
 #      http://www.apache.org/licenses/LICENSE-2.0
-#  
-#  or in the "license" file accompanying this file. This file is distributed 
-#  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either 
-#  express or implied. See the License for the specific language governing 
+#
+#  or in the "license" file accompanying this file. This file is distributed
+#  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
+#  express or implied. See the License for the specific language governing
 #  permissions and limitations under the License.
-
-import boto3
 import inspect
-import os
+
 import tensorflow as tf
-import tf_container.s3_fs as s3_fs
-from tf_container.run import logger
 from tensorflow.contrib.learn import RunConfig, Experiment
 from tensorflow.contrib.learn.python.learn import learn_runner
 from tensorflow.contrib.learn.python.learn.utils import saved_model_export_utils
 from tensorflow.contrib.training import HParams
 
+import tf_container.s3_fs as s3_fs
+from tf_container.run import logger
+
 
 class Trainer(object):
     DEFAULT_TRAINING_CHANNEL = 'training'
@@ -73,7 +72,7 @@ def __init__(self,
         self.customer_params = customer_params
 
         if model_path.startswith('s3://'):
-            s3_fs.configure_s3_fs(model_path)
+            s3_fs.configure_s3_fs(model_path, region_name=customer_params.get('sagemaker_region'))
 
     def _get_task_type(self, masters):
         if self.current_host in masters:

src/tf_container/s3_fs.py

@@ -3,9 +3,7 @@
 import container_support as cs
 
 
-def configure_s3_fs(checkpoint_path):
-    # If env variable is not set, defaults to None, which will use the global endpoint.
-    region_name = os.environ.get('AWS_REGION')
+def configure_s3_fs(checkpoint_path, region_name=None):
     s3 = boto3.client('s3', region_name=region_name)
 
     # We get the AWS region of the checkpoint bucket, which may be different from

src/tf_container/serve.py

@@ -10,27 +10,26 @@
 #  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
 #  express or implied. See the License for the specific language governing
 #  permissions and limitations under the License.
-
+import csv
 import json
+import os
 import shutil
 import subprocess
+import time
+
 import boto3
-import container_support as cs
 import google.protobuf.json_format as json_format
-import os
-
 from grpc import StatusCode
 from grpc.framework.interfaces.face.face import AbortionError
-from tensorflow.core.framework import tensor_pb2
-from tf_container import proxy_client
 from six import StringIO
-import csv
+from tensorflow.core.framework import tensor_pb2
+
+import container_support as cs
 from container_support.serving import UnsupportedContentTypeError, UnsupportedAcceptTypeError, \
                                       JSON_CONTENT_TYPE, CSV_CONTENT_TYPE, \
                                       OCTET_STREAM_CONTENT_TYPE, ANY_CONTENT_TYPE
+from tf_container import proxy_client
 from tf_container.run import logger
-import time
-
 
 TF_SERVING_PORT = 9000
 GENERIC_MODEL_NAME = "generic_model"

src/tf_container/train_entry_point.py

@@ -10,19 +10,18 @@
 #  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
 #  express or implied. See the License for the specific language governing
 #  permissions and limitations under the License.
-
 import argparse
 import json
 import os
 import subprocess
 import time
 from threading import Thread
 
+import boto3
 import tensorflow as tf
 
 import container_support as cs
 import tf_container.run
-import tf_container.s3_fs as s3_fs
 import tf_container.serve as serve
 
 _logger = tf_container.run.get_logger()
@@ -165,7 +164,7 @@ def train():
 
     # only the master should export the model at the end of the execution
     if checkpoint_dir != env.model_dir and train_wrapper.task_type == 'master' and train_wrapper.saves_training():
-        serve.export_saved_model(checkpoint_dir, env.model_dir)
+        serve.export_saved_model(checkpoint_dir, env.model_dir, s3=boto3.client('s3', region_name=env.sagemaker_region))
 
     if train_wrapper.task_type != 'master':
         _wait_until_master_is_down(_get_master(tf_config))

src/tf_container/trainer.py

@@ -1,20 +1,19 @@
 #  Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
-#  
+#
 #  Licensed under the Apache License, Version 2.0 (the "License").
 #  You may not use this file except in compliance with the License.
 #  A copy of the License is located at
-#  
+#
 #      http://www.apache.org/licenses/LICENSE-2.0
-#  
-#  or in the "license" file accompanying this file. This file is distributed 
-#  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either 
-#  express or implied. See the License for the specific language governing 
+#
+#  or in the "license" file accompanying this file. This file is distributed
+#  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
+#  express or implied. See the License for the specific language governing
 #  permissions and limitations under the License.
-
-import boto3
 import inspect
-import os
+
 import tensorflow as tf
+
 from tf_container.run import logger
 import tf_container.s3_fs as s3_fs
 
@@ -62,7 +61,7 @@ def __init__(self,
         self.customer_params = customer_params
 
         if model_path.startswith('s3://'):
-            s3_fs.configure_s3_fs(model_path)
+            s3_fs.configure_s3_fs(model_path, region_name=customer_params.get('sagemaker_region'))
 
     def train(self):
         run_config = self._build_run_config()

test/unit/test_experiment_trainer.py

@@ -1,14 +1,14 @@
 #  Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
-#  
+#
 #  Licensed under the Apache License, Version 2.0 (the "License").
 #  You may not use this file except in compliance with the License.
 #  A copy of the License is located at
-#  
+#
 #      http://www.apache.org/licenses/LICENSE-2.0
-#  
-#  or in the "license" file accompanying this file. This file is distributed 
-#  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either 
-#  express or implied. See the License for the specific language governing 
+#
+#  or in the "license" file accompanying this file. This file is distributed
+#  on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
+#  express or implied. See the License for the specific language governing
 #  permissions and limitations under the License.
 
 import pytest
@@ -112,12 +112,13 @@ def test_build_tf_config_with_multiple_hosts(trainer):
 @patch('botocore.session.get_session')
 @patch('os.environ')
 def test_configure_s3_file_system(os_env, botocore, boto_client, trainer):
-    region = os_env.get('AWS_REGION')
+    region = 'my-region'
 
     trainer.Trainer(customer_script=mock_script,
                     current_host=current_host,
                     hosts=hosts,
-                    model_path='s3://my/s3/path')
+                    model_path='s3://my/s3/path',
+                    customer_params={'sagemaker_region': region})
 
     boto_client.assert_called_once_with('s3', region_name=region)
     boto_client('s3', region_name=region).get_bucket_location.assert_called_once_with(Bucket='my')

test/unit/test_trainer.py

@@ -186,7 +186,7 @@ def test_user_model_fn(modules, trainer):
     estimator = trainer._build_estimator(fake_run_config)
 
     estimator_mock = modules.estimator.Estimator
-    # Verify that _model_fn passed to Estimator correctly passes args through to user script model_fn 
+    # Verify that _model_fn passed to Estimator correctly passes args through to user script model_fn
     estimator_mock.assert_called_with(model_fn=ANY, params=expected_hps, config=fake_run_config)
     _, kwargs, = estimator_mock.call_args
     kwargs['model_fn'](1, 2, 3, 4)
@@ -392,12 +392,13 @@ def test_build_tf_config_with_multiple_hosts(trainer):
 @patch('botocore.session.get_session')
 @patch('os.environ')
 def test_configure_s3_file_system(os_env, botocore, boto_client, trainer_module):
-    region = os_env.get('AWS_REGION')
+    region = 'my-region'
 
     trainer_module.Trainer(customer_script=MOCK_SCRIPT,
                            current_host=CURRENT_HOST,
                            hosts=HOSTS,
-                           model_path='s3://my/s3/path')
+                           model_path='s3://my/s3/path',
+                           customer_params={'sagemaker_region': region})
 
     boto_client.assert_called_once_with('s3', region_name=region)
     boto_client('s3', region_name=region).get_bucket_location.assert_called_once_with(Bucket='my')