Support optional input channels in local mode.

Author: nadiaya

CHANGELOG.rst

@@ -2,6 +2,11 @@
 CHANGELOG
 =========
 
+1.14.1.dev
+==========
+
+* enhancement: Local Mode: support optional input channels
+
 1.14.0
 ======
 

src/sagemaker/local/image.py

@@ -262,7 +262,6 @@ def write_config_files(self, host, hyperparameters, input_data_config):
             'hosts': self.hosts
         }
 
-        print(input_data_config)
         json_input_data_config = {}
         for c in input_data_config:
             channel_name = c['ChannelName']

src/sagemaker/local/local_session.py

@@ -53,8 +53,8 @@ def __init__(self, sagemaker_session=None):
         """
         self.sagemaker_session = sagemaker_session or LocalSession()
 
-    def create_training_job(self, TrainingJobName, AlgorithmSpecification, InputDataConfig, OutputDataConfig,
-                            ResourceConfig, **kwargs):
+    def create_training_job(self, TrainingJobName, AlgorithmSpecification, OutputDataConfig,
+                            ResourceConfig, InputDataConfig=None, **kwargs):
         """
         Create a training job in Local Mode
         Args:
@@ -66,7 +66,7 @@ def create_training_job(self, TrainingJobName, AlgorithmSpecification, InputData
             HyperParameters (dict) [optional]: Specifies these algorithm-specific parameters to influence the quality of
                 the final model.
         """
-
+        InputDataConfig = InputDataConfig or {}
         container = _SageMakerContainer(ResourceConfig['InstanceType'], ResourceConfig['InstanceCount'],
                                         AlgorithmSpecification['TrainingImage'], self.sagemaker_session)
         training_job = _LocalTrainingJob(container)

tests/unit/test_local_session.py

@@ -61,8 +61,8 @@ def test_create_training_job(train, LocalSession):
     resource_config = {'InstanceType': 'local', 'InstanceCount': instance_count}
     hyperparameters = {'a': 1, 'b': 'bee'}
 
-    local_sagemaker_client.create_training_job('my-training-job', algo_spec, input_data_config,
-                                               output_data_config, resource_config, HyperParameters=hyperparameters)
+    local_sagemaker_client.create_training_job('my-training-job', algo_spec, output_data_config, resource_config,
+                                               InputDataConfig=input_data_config, HyperParameters=hyperparameters)
 
     expected = {
         'ResourceConfig': {'InstanceCount': instance_count},
@@ -111,8 +111,8 @@ def test_create_training_job_invalid_data_source(train, LocalSession):
     hyperparameters = {'a': 1, 'b': 'bee'}
 
     with pytest.raises(ValueError):
-        local_sagemaker_client.create_training_job('my-training-job', algo_spec, input_data_config,
-                                                   output_data_config, resource_config, HyperParameters=hyperparameters)
+        local_sagemaker_client.create_training_job('my-training-job', algo_spec, output_data_config, resource_config,
+                                                   InputDataConfig=input_data_config, HyperParameters=hyperparameters)
 
 
 @patch('sagemaker.local.image._SageMakerContainer.train', return_value="/some/path/to/model")
@@ -141,8 +141,8 @@ def test_create_training_job_not_fully_replicated(train, LocalSession):
     hyperparameters = {'a': 1, 'b': 'bee'}
 
     with pytest.raises(RuntimeError):
-        local_sagemaker_client.create_training_job('my-training-job', algo_spec, input_data_config,
-                                                   output_data_config, resource_config, HyperParameters=hyperparameters)
+        local_sagemaker_client.create_training_job('my-training-job', algo_spec, output_data_config, resource_config,
+                                                   InputDataConfig=input_data_config, HyperParameters=hyperparameters)
 
 
 @patch('sagemaker.local.local_session.LocalSession')