Revert the PR changes 5122 (#5134)

rsareddy0329 · Roja Reddy Sareddy · zhaoqizqwang · web-flow · commit 06801a4936be · 2025-04-19T19:11:58.000-07:00
* change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * change: Allow telemetry only in supported regions * documentation: Removed a line about python version requirements of training script which can misguide users.Training script can be of latest version based on the support provided by framework_version of the container * feature: Enabled update_endpoint through model_builder * fix: fix unit test, black-check, pylint errors * fix: fix black-check, pylint errors * fix:Added handler for pipeline variable while creating process job * fix: Added handler for pipeline variable while creating process job * Revert the PR changes: #5122, due to issue https://t.corp.amazon.com/P223568185/overview * Fix: fix the issue, https://t.corp.amazon.com/P223568185/communication * Revert PR 5122 changes, due to issues with other processor codeflows --------- Co-authored-by: Roja Reddy Sareddy <rsareddy@amazon.com> Co-authored-by: Zhaoqi <jzhaoqwa@amazon.com>
diff --git a/src/sagemaker/processing.py b/src/sagemaker/processing.py
@@ -17,7 +17,6 @@
 and interpretation on Amazon SageMaker.
 """
 from __future__ import absolute_import
-import json
 import logging
 import os
 import pathlib
@@ -315,16 +314,6 @@ def _normalize_args(
                 + "rather than a pipeline variable"
             )
 
-        if arguments is not None:
-            processed_arguments = []
-            for arg in arguments:
-                if isinstance(arg, PipelineVariable):
-                    processed_value = json.dumps(arg.expr)
-                    processed_arguments.append(processed_value)
-                else:
-                    processed_arguments.append(arg)
-            arguments = processed_arguments
-
         self._current_job_name = self._generate_current_job_name(job_name=job_name)
 
         inputs_with_code = self._include_code_in_inputs(inputs, code, kms_key)
diff --git a/tests/unit/sagemaker/workflow/test_processing_step.py b/tests/unit/sagemaker/workflow/test_processing_step.py
@@ -825,13 +825,6 @@ def test_spark_processor(spark_processor, processing_input, pipeline_session):
     processor.sagemaker_session = pipeline_session
     processor.role = ROLE
 
-    arguments_output = [
-        "--input",
-        "input-data-uri",
-        "--output",
-        '{"Get": "Parameters.MyArgOutput"}',
-    ]
-
     run_inputs["inputs"] = processing_input
 
     step_args = processor.run(**run_inputs)
@@ -842,7 +835,7 @@ def test_spark_processor(spark_processor, processing_input, pipeline_session):
 
     step_args = get_step_args_helper(step_args, "Processing")
 
-    assert step_args["AppSpecification"]["ContainerArguments"] == arguments_output
+    assert step_args["AppSpecification"]["ContainerArguments"] == run_inputs["arguments"]
 
     entry_points = step_args["AppSpecification"]["ContainerEntrypoint"]
     entry_points_expr = []
@@ -1027,13 +1020,6 @@ def test_spark_processor_local_code(spark_processor, processing_input, pipeline_
     processor.sagemaker_session = pipeline_session
     processor.role = ROLE
 
-    arguments_output = [
-        "--input",
-        "input-data-uri",
-        "--output",
-        '{"Get": "Parameters.MyArgOutput"}',
-    ]
-
     run_inputs["inputs"] = processing_input
 
     step_args = processor.run(**run_inputs)
@@ -1044,7 +1030,7 @@ def test_spark_processor_local_code(spark_processor, processing_input, pipeline_
 
     step_args = get_step_args_helper(step_args, "Processing")
 
-    assert step_args["AppSpecification"]["ContainerArguments"] == arguments_output
+    assert step_args["AppSpecification"]["ContainerArguments"] == run_inputs["arguments"]
 
     entry_points = step_args["AppSpecification"]["ContainerEntrypoint"]
     entry_points_expr = []
diff --git a/tests/unit/test_processing.py b/tests/unit/test_processing.py
@@ -46,9 +46,8 @@
 from sagemaker.fw_utils import UploadedCode
 from sagemaker.workflow.pipeline_context import PipelineSession, _PipelineConfig
 from sagemaker.workflow.functions import Join
-from sagemaker.workflow.execution_variables import ExecutionVariable, ExecutionVariables
+from sagemaker.workflow.execution_variables import ExecutionVariables
 from tests.unit import SAGEMAKER_CONFIG_PROCESSING_JOB
-from sagemaker.workflow.parameters import ParameterString
 
 BUCKET_NAME = "mybucket"
 REGION = "us-west-2"
@@ -1718,249 +1717,3 @@ def _get_describe_response_inputs_and_ouputs():
         "ProcessingInputs": _get_expected_args_all_parameters(None)["inputs"],
         "ProcessingOutputConfig": _get_expected_args_all_parameters(None)["output_config"],
     }
-
-
-# Parameters
-def _get_data_inputs_with_parameters():
-    return [
-        ProcessingInput(
-            source=ParameterString(name="input_data", default_value="s3://dummy-bucket/input"),
-            destination="/opt/ml/processing/input",
-            input_name="input-1",
-        )
-    ]
-
-
-def _get_data_outputs_with_parameters():
-    return [
-        ProcessingOutput(
-            source="/opt/ml/processing/output",
-            destination=ParameterString(
-                name="output_data", default_value="s3://dummy-bucket/output"
-            ),
-            output_name="output-1",
-        )
-    ]
-
-
-def _get_expected_args_with_parameters(job_name):
-    return {
-        "inputs": [
-            {
-                "InputName": "input-1",
-                "S3Input": {
-                    "S3Uri": "s3://dummy-bucket/input",
-                    "LocalPath": "/opt/ml/processing/input",
-                    "S3DataType": "S3Prefix",
-                    "S3InputMode": "File",
-                    "S3DataDistributionType": "FullyReplicated",
-                    "S3CompressionType": "None",
-                },
-            }
-        ],
-        "output_config": {
-            "Outputs": [
-                {
-                    "OutputName": "output-1",
-                    "S3Output": {
-                        "S3Uri": "s3://dummy-bucket/output",
-                        "LocalPath": "/opt/ml/processing/output",
-                        "S3UploadMode": "EndOfJob",
-                    },
-                }
-            ]
-        },
-        "job_name": job_name,
-        "resources": {
-            "ClusterConfig": {
-                "InstanceType": "ml.m4.xlarge",
-                "InstanceCount": 1,
-                "VolumeSizeInGB": 100,
-                "VolumeKmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/volume-kms-key",
-            }
-        },
-        "stopping_condition": {"MaxRuntimeInSeconds": 3600},
-        "app_specification": {
-            "ImageUri": "custom-image-uri",
-            "ContainerArguments": [
-                "--input-data",
-                "s3://dummy-bucket/input-param",
-                "--output-path",
-                "s3://dummy-bucket/output-param",
-            ],
-            "ContainerEntrypoint": ["python3"],
-        },
-        "environment": {"my_env_variable": "my_env_variable_value"},
-        "network_config": {
-            "EnableNetworkIsolation": True,
-            "EnableInterContainerTrafficEncryption": True,
-            "VpcConfig": {
-                "Subnets": ["my_subnet_id"],
-                "SecurityGroupIds": ["my_security_group_id"],
-            },
-        },
-        "role_arn": "dummy/role",
-        "tags": [{"Key": "my-tag", "Value": "my-tag-value"}],
-        "experiment_config": {"ExperimentName": "AnExperiment"},
-    }
-
-
-@patch("os.path.exists", return_value=True)
-@patch("os.path.isfile", return_value=True)
-@patch("sagemaker.utils.repack_model")
-@patch("sagemaker.utils.create_tar_file")
-@patch("sagemaker.session.Session.upload_data")
-def test_script_processor_with_parameter_string(
-    upload_data_mock,
-    create_tar_file_mock,
-    repack_model_mock,
-    exists_mock,
-    isfile_mock,
-    sagemaker_session,
-):
-    """Test ScriptProcessor with ParameterString arguments"""
-    upload_data_mock.return_value = "s3://mocked_s3_uri_from_upload_data"
-
-    # Setup processor
-    processor = ScriptProcessor(
-        role="arn:aws:iam::012345678901:role/SageMakerRole",  # Updated role ARN
-        image_uri="custom-image-uri",
-        command=["python3"],
-        instance_type="ml.m4.xlarge",
-        instance_count=1,
-        volume_size_in_gb=100,
-        volume_kms_key="arn:aws:kms:us-west-2:012345678901:key/volume-kms-key",
-        output_kms_key="arn:aws:kms:us-west-2:012345678901:key/output-kms-key",
-        max_runtime_in_seconds=3600,
-        base_job_name="test_processor",
-        env={"my_env_variable": "my_env_variable_value"},
-        tags=[{"Key": "my-tag", "Value": "my-tag-value"}],
-        network_config=NetworkConfig(
-            subnets=["my_subnet_id"],
-            security_group_ids=["my_security_group_id"],
-            enable_network_isolation=True,
-            encrypt_inter_container_traffic=True,
-        ),
-        sagemaker_session=sagemaker_session,
-    )
-
-    input_param = ParameterString(name="input_param", default_value="s3://dummy-bucket/input-param")
-    output_param = ParameterString(
-        name="output_param", default_value="s3://dummy-bucket/output-param"
-    )
-    exec_var = ExecutionVariable(name="ExecutionTest")
-    join_var = Join(on="/", values=["s3://bucket", "prefix", "file.txt"])
-    dummy_str_var = "test-variable"
-
-    # Define expected arguments
-    expected_args = {
-        "inputs": [
-            {
-                "InputName": "input-1",
-                "AppManaged": False,
-                "S3Input": {
-                    "S3Uri": ParameterString(
-                        name="input_data", default_value="s3://dummy-bucket/input"
-                    ),
-                    "LocalPath": "/opt/ml/processing/input",
-                    "S3DataType": "S3Prefix",
-                    "S3InputMode": "File",
-                    "S3DataDistributionType": "FullyReplicated",
-                    "S3CompressionType": "None",
-                },
-            },
-            {
-                "InputName": "code",
-                "AppManaged": False,
-                "S3Input": {
-                    "S3Uri": "s3://mocked_s3_uri_from_upload_data",
-                    "LocalPath": "/opt/ml/processing/input/code",
-                    "S3DataType": "S3Prefix",
-                    "S3InputMode": "File",
-                    "S3DataDistributionType": "FullyReplicated",
-                    "S3CompressionType": "None",
-                },
-            },
-        ],
-        "output_config": {
-            "Outputs": [
-                {
-                    "OutputName": "output-1",
-                    "AppManaged": False,
-                    "S3Output": {
-                        "S3Uri": ParameterString(
-                            name="output_data", default_value="s3://dummy-bucket/output"
-                        ),
-                        "LocalPath": "/opt/ml/processing/output",
-                        "S3UploadMode": "EndOfJob",
-                    },
-                }
-            ],
-            "KmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/output-kms-key",
-        },
-        "job_name": "test_job",
-        "resources": {
-            "ClusterConfig": {
-                "InstanceType": "ml.m4.xlarge",
-                "InstanceCount": 1,
-                "VolumeSizeInGB": 100,
-                "VolumeKmsKeyId": "arn:aws:kms:us-west-2:012345678901:key/volume-kms-key",
-            }
-        },
-        "stopping_condition": {"MaxRuntimeInSeconds": 3600},
-        "app_specification": {
-            "ImageUri": "custom-image-uri",
-            "ContainerArguments": [
-                "--input-data",
-                '{"Get": "Parameters.input_param"}',
-                "--output-path",
-                '{"Get": "Parameters.output_param"}',
-                "--exec-arg",
-                '{"Get": "Execution.ExecutionTest"}',
-                "--join-arg",
-                '{"Std:Join": {"On": "/", "Values": ["s3://bucket", "prefix", "file.txt"]}}',
-                "--string-param",
-                "test-variable",
-            ],
-            "ContainerEntrypoint": ["python3", "/opt/ml/processing/input/code/processing_code.py"],
-        },
-        "environment": {"my_env_variable": "my_env_variable_value"},
-        "network_config": {
-            "EnableNetworkIsolation": True,
-            "EnableInterContainerTrafficEncryption": True,
-            "VpcConfig": {
-                "SecurityGroupIds": ["my_security_group_id"],
-                "Subnets": ["my_subnet_id"],
-            },
-        },
-        "role_arn": "arn:aws:iam::012345678901:role/SageMakerRole",
-        "tags": [{"Key": "my-tag", "Value": "my-tag-value"}],
-        "experiment_config": {"ExperimentName": "AnExperiment"},
-    }
-
-    # Run processor
-    processor.run(
-        code="/local/path/to/processing_code.py",
-        inputs=_get_data_inputs_with_parameters(),
-        outputs=_get_data_outputs_with_parameters(),
-        arguments=[
-            "--input-data",
-            input_param,
-            "--output-path",
-            output_param,
-            "--exec-arg",
-            exec_var,
-            "--join-arg",
-            join_var,
-            "--string-param",
-            dummy_str_var,
-        ],
-        wait=True,
-        logs=False,
-        job_name="test_job",
-        experiment_config={"ExperimentName": "AnExperiment"},
-    )
-
-    # Assert
-    sagemaker_session.process.assert_called_with(**expected_args)
-    assert "test_job" in processor._current_job_name
