fix: add hyperparameter tuning test

.flake8

@@ -1,3 +1,3 @@
 [flake8]
-application_import_names = sagemaker_tensorflow_container, test, utils
+application_import_names = sagemaker_tensorflow_container, test, timeout, utils
 import-order-style = google

test/integration/sagemaker/test_mnist.py

@@ -17,14 +17,16 @@
 import boto3
 import pytest
 from sagemaker.tensorflow import TensorFlow
+from sagemaker.tuner import HyperparameterTuner, IntegerParameter
 from six.moves.urllib.parse import urlparse
 
 from test.integration.utils import processor, py_version, unique_name_from_base  # noqa: F401
+from timeout import timeout
 
 
 @pytest.mark.deploy_test
 def test_mnist(sagemaker_session, ecr_image, instance_type, framework_version):
-    resource_path = os.path.join(os.path.dirname(__file__), '../..', 'resources')
+    resource_path = os.path.join(os.path.dirname(__file__), '..', '..', 'resources')
     script = os.path.join(resource_path, 'mnist', 'mnist.py')
     estimator = TensorFlow(entry_point=script,
                            role='SageMakerRole',
@@ -42,7 +44,7 @@ def test_mnist(sagemaker_session, ecr_image, instance_type, framework_version):
 
 
 def test_distributed_mnist_no_ps(sagemaker_session, ecr_image, instance_type, framework_version):
-    resource_path = os.path.join(os.path.dirname(__file__), '../..', 'resources')
+    resource_path = os.path.join(os.path.dirname(__file__), '..', '..', 'resources')
     script = os.path.join(resource_path, 'mnist', 'mnist.py')
     estimator = TensorFlow(entry_point=script,
                            role='SageMakerRole',
@@ -110,6 +112,40 @@ def test_s3_plugin(sagemaker_session, ecr_image, instance_type, region, framewor
     _assert_checkpoint_exists(region, estimator.model_dir, 200)
 
 
+def test_tuning(sagemaker_session, ecr_image, instance_type, framework_version):
+    resource_path = os.path.join(os.path.dirname(__file__), '..', '..', 'resources')
+    script = os.path.join(resource_path, 'mnist', 'mnist.py')
+
+    estimator = TensorFlow(entry_point=script,
+                           role='SageMakerRole',
+                           train_instance_type=instance_type,
+                           train_instance_count=1,
+                           sagemaker_session=sagemaker_session,
+                           image_name=ecr_image,
+                           framework_version=framework_version,
+                           script_mode=True)
+
+    hyperparameter_ranges = {'epochs': IntegerParameter(1, 2)}
+    objective_metric_name = 'accuracy'
+    metric_definitions = [{'Name': objective_metric_name, 'Regex': 'accuracy = ([0-9\\.]+)'}]
+
+    tuner = HyperparameterTuner(estimator,
+                                objective_metric_name,
+                                hyperparameter_ranges,
+                                metric_definitions,
+                                max_jobs=2,
+                                max_parallel_jobs=2)
+
+    with timeout(minutes=20):
+        inputs = estimator.sagemaker_session.upload_data(
+            path=os.path.join(resource_path, 'mnist', 'data'),
+            key_prefix='scriptmode/mnist')
+
+        tuning_job_name = unique_name_from_base('test-tf-sm-tuning', max_length=32)
+        tuner.fit(inputs, job_name=tuning_job_name)
+        tuner.wait()
+
+
 def _assert_checkpoint_exists(region, model_dir, checkpoint_number):
     _assert_s3_file_exists(region, os.path.join(model_dir, 'graph.pbtxt'))
     _assert_s3_file_exists(region,

test/integration/sagemaker/timeout.py

@@ -0,0 +1,50 @@
+# Copyright 2019 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
+# permissions and limitations under the License.
+from __future__ import absolute_import
+
+from contextlib import contextmanager
+import logging
+import signal
+
+LOGGER = logging.getLogger('timeout')
+
+
+class TimeoutError(Exception):
+    pass
+
+
+@contextmanager
+def timeout(seconds=0, minutes=0, hours=0):
+    """Add a signal-based timeout to any block of code.
+    If multiple time units are specified, they will be added together to determine time limit.
+    Usage:
+    with timeout(seconds=5):
+        my_slow_function(...)
+    Args:
+        - seconds: The time limit, in seconds.
+        - minutes: The time limit, in minutes.
+        - hours: The time limit, in hours.
+    """
+
+    limit = seconds + 60 * minutes + 3600 * hours
+
+    def handler(signum, frame):
+        raise TimeoutError('timed out after {} seconds'.format(limit))
+
+    try:
+        signal.signal(signal.SIGALRM, handler)
+        signal.alarm(limit)
+
+        yield
+    finally:
+        signal.alarm(0)