Add another unit test

This should increase code coverage by testing if the
optional training parameters are set by the user.

Author: laurenyu

tests/unit/test_session.py

@@ -229,6 +229,39 @@ def test_train_pack_to_request(sagemaker_session):
         'create_training_job', (), DEFAULT_EXPECTED_TRAIN_JOB_ARGS)
 
 
+def test_train_pack_to_request_with_optional_params(sagemaker_session):
+    in_config = [{
+        'ChannelName': 'training',
+        'DataSource': {
+            'S3DataSource': {
+                'S3DataDistributionType': 'FullyReplicated',
+                'S3DataType': 'S3Prefix',
+                'S3Uri': S3_INPUT_URI
+            }
+        }
+    }]
+
+    out_config = {'S3OutputPath': S3_OUTPUT}
+
+    resource_config = {'InstanceCount': INSTANCE_COUNT,
+                       'InstanceType': INSTANCE_TYPE,
+                       'VolumeSizeInGB': MAX_SIZE}
+
+    stop_cond = {'MaxRuntimeInSeconds': MAX_TIME}
+
+    hyperparameters = {'foo': 'bar'}
+    tags = [{'Name': 'some-tag', 'Value': 'value-for-tag'}]
+
+    sagemaker_session.train(image=IMAGE, input_mode='File', input_config=in_config, role=EXPANDED_ROLE,
+                            job_name=JOB_NAME, output_config=out_config, resource_config=resource_config,
+                            hyperparameters=hyperparameters, stop_condition=stop_cond, tags=tags)
+
+    _, _, actual_train_args = sagemaker_session.sagemaker_client.method_calls[0]
+
+    assert actual_train_args['HyperParameters'] == hyperparameters
+    assert actual_train_args['Tags'] == tags
+
+
 @patch('sys.stdout', new_callable=io.BytesIO if six.PY2 else io.StringIO)
 def test_color_wrap(bio):
     color_wrap = sagemaker.logs.ColorWrap()