Merge branch 'master' into fix/estimator-hyperparameters

Author: evakravi

src/sagemaker/local/pipeline.py

@@ -89,16 +89,15 @@ def _parse_arguments(self, obj, step_name):
         if isinstance(obj, dict):
             obj_copy = deepcopy(obj)
             for k, v in obj.items():
-                if isinstance(v, dict):
-                    obj_copy[k] = self._parse_arguments(v, step_name)
-                elif isinstance(v, list):
-                    list_copy = []
-                    for item in v:
-                        list_copy.append(self._parse_arguments(item, step_name))
-                    obj_copy[k] = list_copy
-                elif isinstance(v, PipelineVariable):
-                    obj_copy[k] = self.evaluate_pipeline_variable(v, step_name)
+                obj_copy[k] = self._parse_arguments(v, step_name)
             return obj_copy
+        if isinstance(obj, list):
+            list_copy = []
+            for item in obj:
+                list_copy.append(self._parse_arguments(item, step_name))
+            return list_copy
+        if isinstance(obj, PipelineVariable):
+            return self.evaluate_pipeline_variable(obj, step_name)
         return obj
 
     def evaluate_pipeline_variable(self, pipeline_variable, step_name):

tests/integ/test_local_mode.py

@@ -35,7 +35,7 @@
 from sagemaker.workflow.pipeline import Pipeline
 from sagemaker.workflow.steps import TrainingStep, ProcessingStep, TransformStep
 from sagemaker.workflow.model_step import ModelStep
-from sagemaker.workflow.parameters import ParameterInteger
+from sagemaker.workflow.parameters import ParameterInteger, ParameterString
 from sagemaker.workflow.condition_step import ConditionStep
 from sagemaker.workflow.fail_step import FailStep
 from sagemaker.workflow.conditions import ConditionLessThanOrEqualTo
@@ -496,6 +496,7 @@ def test_local_processing_script_processor(sagemaker_local_session, sklearn_imag
 
 @pytest.mark.local_mode
 def test_local_pipeline_with_processing_step(sklearn_latest_version, local_pipeline_session):
+    string_container_arg = ParameterString(name="ProcessingContainerArg", default_value="foo")
     sklearn_processor = SKLearnProcessor(
         framework_version=sklearn_latest_version,
         role="SageMakerRole",
@@ -509,6 +510,7 @@ def test_local_pipeline_with_processing_step(sklearn_latest_version, local_pipel
     processing_args = sklearn_processor.run(
         code=script_path,
         inputs=[ProcessingInput(source=input_file_path, destination="/opt/ml/processing/inputs/")],
+        arguments=["--container_arg", string_container_arg],
     )
     processing_step = ProcessingStep(
         name="sklearn_processor_local_pipeline", step_args=processing_args
@@ -517,6 +519,7 @@ def test_local_pipeline_with_processing_step(sklearn_latest_version, local_pipel
         name="local_pipeline_processing",
         steps=[processing_step],
         sagemaker_session=local_pipeline_session,
+        parameters=[string_container_arg],
     )
     pipeline.create("SageMakerRole", "pipeline for sdk integ testing")