fix: improve Pipeline workflow unit test branch coverage

fix: Update to use the new JsonGet constructor

fix: Update to use the new JsonGet constructor

Author: Dewen Qi

src/sagemaker/workflow/_repack_model.py

@@ -34,7 +34,7 @@
 from distutils.dir_util import copy_tree
 
 
-def repack(inference_script, model_archive, dependencies=None, source_dir=None):
+def repack(inference_script, model_archive, dependencies=None, source_dir=None):  # pragma: no cover
     """Repack custom dependencies and code into an existing model TAR archive
 
     Args:
@@ -95,7 +95,7 @@ def repack(inference_script, model_archive, dependencies=None, source_dir=None):
         copy_tree(src_dir, "/opt/ml/model")
 
 
-if __name__ == "__main__":
+if __name__ == "__main__":  # pragma: no cover
     parser = argparse.ArgumentParser()
     parser.add_argument("--inference_script", type=str, default="inference.py")
     parser.add_argument("--dependencies", type=str, default=None)

src/sagemaker/workflow/_utils.py

@@ -54,7 +54,7 @@ def __init__(
         name: str,
         sagemaker_session,
         role,
-        model_data: str,
+        model_data: Union[str, Properties],
         entry_point: str,
         display_name: str = None,
         description: str = None,
@@ -79,8 +79,8 @@ def __init__(
                     endpoints use this role to access training data and model
                     artifacts. After the endpoint is created, the inference code
                     might use the IAM role, if it needs to access an AWS resource.
-            model_data (str): The S3 location of a SageMaker model data
-                    ``.tar.gz`` file (default: None).
+            model_data (str or Properties): The S3 location of a SageMaker model data
+                    ``.tar.gz`` file.
             entry_point (str): Path (absolute or relative) to the local Python
                     source file which should be executed as the entry point to
                     inference. If ``source_dir`` is specified, then ``entry_point``

src/sagemaker/workflow/condition_step.py

@@ -95,7 +95,7 @@ def properties(self):
 
 
 @attr.s
-class JsonGet(Expression):
+class JsonGet(Expression):  # pragma: no cover
     """Get JSON properties from PropertyFiles.
 
     Attributes:

src/sagemaker/workflow/functions.py

@@ -75,8 +75,8 @@ class JsonGet(Expression):
     @property
     def expr(self):
         """The expression dict for a `JsonGet` function."""
-        if not isinstance(self.step_name, str):
-            raise ValueError("Please give step name as a string")
+        if not isinstance(self.step_name, str) or not self.step_name:
+            raise ValueError("Please give a valid step name as a string")
 
         if isinstance(self.property_file, PropertyFile):
             name = self.property_file.name

src/sagemaker/workflow/lambda_step.py

@@ -161,8 +161,8 @@ def _get_function_arn(self):
             partition = "aws"
 
         if self.lambda_func.function_arn is None:
+            account_id = self.lambda_func.session.account_id()
             try:
-                account_id = self.lambda_func.session.account_id()
                 response = self.lambda_func.create()
                 return response["FunctionArn"]
             except ValueError as error:

src/sagemaker/workflow/step_collections.py

@@ -318,15 +318,15 @@ def __init__(
         """
         steps = []
         if "entry_point" in kwargs:
-            entry_point = kwargs["entry_point"]
-            source_dir = kwargs.get("source_dir")
-            dependencies = kwargs.get("dependencies")
+            entry_point = kwargs.get("entry_point")
+            source_dir = kwargs.get("source_dir", None)
+            dependencies = kwargs.get("dependencies", None)
             repack_model_step = _RepackModelStep(
                 name=f"{name}RepackModel",
                 depends_on=depends_on,
                 retry_policies=repack_model_step_retry_policies,
                 sagemaker_session=estimator.sagemaker_session,
-                role=estimator.sagemaker_session,
+                role=estimator.role,
                 model_data=model_data,
                 entry_point=entry_point,
                 source_dir=source_dir,
@@ -352,7 +352,11 @@ def predict_wrapper(endpoint, session):
             vpc_config=None,
             sagemaker_session=estimator.sagemaker_session,
             role=estimator.role,
-            **kwargs,
+            env=kwargs.get("env", None),
+            name=kwargs.get("name", None),
+            enable_network_isolation=kwargs.get("enable_network_isolation", None),
+            model_kms_key=kwargs.get("model_kms_key", None),
+            image_config=kwargs.get("image_config", None),
         )
         model_step = CreateModelStep(
             name=f"{name}CreateModelStep",

tests/integ/test_workflow.py

@@ -2763,7 +2763,7 @@ def test_end_to_end_pipeline_successful_execution(
     # define condition step
     cond_lte = ConditionLessThanOrEqualTo(
         left=JsonGet(
-            step=step_eval,
+            step_name=step_eval.name,
             property_file=evaluation_report,
             json_path="regression_metrics.mse.value",
         ),

tests/integ/test_workflow_with_clarify.py

@@ -33,7 +33,8 @@
 from sagemaker.processing import ProcessingInput, ProcessingOutput
 from sagemaker.session import get_execution_role
 from sagemaker.workflow.conditions import ConditionLessThanOrEqualTo
-from sagemaker.workflow.condition_step import ConditionStep, JsonGet
+from sagemaker.workflow.condition_step import ConditionStep
+from sagemaker.workflow.functions import JsonGet
 from sagemaker.workflow.parameters import (
     ParameterInteger,
     ParameterString,
@@ -237,7 +238,7 @@ def test_workflow_with_clarify(
         )
 
         cond_left = JsonGet(
-            step=step_process,
+            step_name=step_process.name,
             property_file="BiasOutput",
             json_path="post_training_bias_metrics.facets.F1[0].metrics[0].value",
         )

tests/unit/test_airflow.py renamed to tests/unit/sagemaker/workflow/test_airflow.py

@@ -13,6 +13,8 @@
 # language governing permissions and limitations under the License.
 from __future__ import absolute_import
 
+import pytest
+
 from sagemaker.workflow.execution_variables import ExecutionVariables
 from sagemaker.workflow.functions import Join, JsonGet
 from sagemaker.workflow.parameters import (
@@ -97,3 +99,23 @@ def test_json_get_expressions():
             "Path": "my-json-path",
         },
     }
+
+
+def test_json_get_expressions_with_invalid_step_name():
+    with pytest.raises(ValueError) as err:
+        JsonGet(
+            step_name="",
+            property_file="my-property-file",
+            json_path="my-json-path",
+        ).expr
+
+    assert "Please give a valid step name as a string" in str(err.value)
+
+    with pytest.raises(ValueError) as err:
+        JsonGet(
+            step_name=ParameterString(name="MyString"),
+            property_file="my-property-file",
+            json_path="my-json-path",
+        ).expr
+
+    assert "Please give a valid step name as a string" in str(err.value)

tests/unit/sagemaker/workflow/test_functions.py

@@ -22,6 +22,7 @@
 from sagemaker.workflow.pipeline import Pipeline
 from sagemaker.workflow.lambda_step import LambdaStep, LambdaOutput, LambdaOutputTypeEnum
 from sagemaker.lambda_helper import Lambda
+from sagemaker.workflow.steps import CacheConfig
 
 
 @pytest.fixture()
@@ -38,10 +39,25 @@ def sagemaker_session():
     return session_mock
 
 
+@pytest.fixture()
+def sagemaker_session_cn():
+    boto_mock = Mock(name="boto_session", region_name="cn-north-1")
+    session_mock = MagicMock(
+        name="sagemaker_session",
+        boto_session=boto_mock,
+        boto_region_name="cn-north-1",
+        config=None,
+        local_mode=False,
+    )
+    session_mock.account_id.return_value = "234567890123"
+    return session_mock
+
+
 def test_lambda_step(sagemaker_session):
     param = ParameterInteger(name="MyInt")
-    outputParam1 = LambdaOutput(output_name="output1", output_type=LambdaOutputTypeEnum.String)
-    outputParam2 = LambdaOutput(output_name="output2", output_type=LambdaOutputTypeEnum.Boolean)
+    output_param1 = LambdaOutput(output_name="output1", output_type=LambdaOutputTypeEnum.String)
+    output_param2 = LambdaOutput(output_name="output2", output_type=LambdaOutputTypeEnum.Boolean)
+    cache_config = CacheConfig(enable_caching=True, expire_after="PT1H")
     lambda_step = LambdaStep(
         name="MyLambdaStep",
         depends_on=["TestStep"],
@@ -52,10 +68,17 @@ def test_lambda_step(sagemaker_session):
         display_name="MyLambdaStep",
         description="MyLambdaStepDescription",
         inputs={"arg1": "foo", "arg2": 5, "arg3": param},
-        outputs=[outputParam1, outputParam2],
+        outputs=[output_param1, output_param2],
+        cache_config=cache_config,
     )
     lambda_step.add_depends_on(["SecondTestStep"])
-    assert lambda_step.to_request() == {
+    pipeline = Pipeline(
+        name="MyPipeline",
+        parameters=[param],
+        steps=[lambda_step],
+        sagemaker_session=sagemaker_session,
+    )
+    assert json.loads(pipeline.definition())["Steps"][0] == {
         "Name": "MyLambdaStep",
         "Type": "Lambda",
         "DependsOn": ["TestStep", "SecondTestStep"],
@@ -66,7 +89,8 @@ def test_lambda_step(sagemaker_session):
             {"OutputName": "output1", "OutputType": "String"},
             {"OutputName": "output2", "OutputType": "Boolean"},
         ],
-        "Arguments": {"arg1": "foo", "arg2": 5, "arg3": param},
+        "Arguments": {"arg1": "foo", "arg2": 5, "arg3": {"Get": "Parameters.MyInt"}},
+        "CacheConfig": {"Enabled": True, "ExpireAfter": "PT1H"},
     }
 
 
@@ -95,8 +119,8 @@ def test_lambda_step_output_expr(sagemaker_session):
 
 def test_pipeline_interpolates_lambda_outputs(sagemaker_session):
     parameter = ParameterString("MyStr")
-    outputParam1 = LambdaOutput(output_name="output1", output_type=LambdaOutputTypeEnum.String)
-    outputParam2 = LambdaOutput(output_name="output2", output_type=LambdaOutputTypeEnum.String)
+    output_param1 = LambdaOutput(output_name="output1", output_type=LambdaOutputTypeEnum.String)
+    output_param2 = LambdaOutput(output_name="output2", output_type=LambdaOutputTypeEnum.String)
     lambda_step1 = LambdaStep(
         name="MyLambdaStep1",
         depends_on=["TestStep"],
@@ -105,7 +129,7 @@ def test_pipeline_interpolates_lambda_outputs(sagemaker_session):
             session=sagemaker_session,
         ),
         inputs={"arg1": "foo"},
-        outputs=[outputParam1],
+        outputs=[output_param1],
     )
     lambda_step2 = LambdaStep(
         name="MyLambdaStep2",
@@ -114,8 +138,8 @@ def test_pipeline_interpolates_lambda_outputs(sagemaker_session):
             function_arn="arn:aws:lambda:us-west-2:123456789012:function:sagemaker_test_lambda",
             session=sagemaker_session,
         ),
-        inputs={"arg1": outputParam1},
-        outputs=[outputParam2],
+        inputs={"arg1": output_param1},
+        outputs=[output_param2],
     )
 
     pipeline = Pipeline(
@@ -207,3 +231,37 @@ def test_lambda_step_without_function_arn(sagemaker_session):
     )
     lambda_step._get_function_arn()
     sagemaker_session.account_id.assert_called_once()
+
+
+def test_lambda_step_without_function_arn_and_with_error(sagemaker_session_cn):
+    lambda_func = MagicMock(
+        function_arn=None,
+        function_name="name",
+        execution_role_arn="arn:aws:lambda:us-west-2:123456789012:execution_role",
+        zipped_code_dir="",
+        handler="",
+        session=sagemaker_session_cn,
+    )
+    # The raised ValueError contains ResourceConflictException
+    lambda_func.create.side_effect = ValueError("ResourceConflictException")
+    lambda_step1 = LambdaStep(
+        name="MyLambdaStep1",
+        depends_on=["TestStep"],
+        lambda_func=lambda_func,
+        inputs={},
+        outputs=[],
+    )
+    function_arn = lambda_step1._get_function_arn()
+    assert function_arn == "arn:aws-cn:lambda:cn-north-1:234567890123:function:name"
+
+    # The raised ValueError does not contain ResourceConflictException
+    lambda_func.create.side_effect = ValueError()
+    lambda_step2 = LambdaStep(
+        name="MyLambdaStep2",
+        depends_on=["TestStep"],
+        lambda_func=lambda_func,
+        inputs={},
+        outputs=[],
+    )
+    with pytest.raises(ValueError):
+        lambda_step2._get_function_arn()