code: def _get_expected_args_modular_code(
      job_name, code_s3_uri=f"s3://{BUCKET_NAME}"
  ):
      return {
          "inputs": [
              {
                  "InputName": "code",
                  "AppManaged": False,
                  "S3Input": {
                      "S3Uri": f"{code_s3_uri}/{job_name}/source/sourcedir.tar.gz",
                      "LocalPath": "/opt/ml/processing/input/code/",
                      "S3DataType": "S3Prefix",
                      "S3InputMode": "File",
                      "S3DataDistributionType": "FullyReplicated",
                      "S3CompressionType": "None",
                  },
              },
              {
                  "InputName": "entrypoint",
                  "AppManaged": False,
                  "S3Input": {
                      "S3Uri": f"{code_s3_uri}/{job_name}/source/runproc.sh",
                      "LocalPath": "/opt/ml/processing/input/entrypoint",
                      "S3DataType": "S3Prefix",
                      "S3InputMode": "File",
                      "S3DataDistributionType": "FullyReplicated",
                      "S3CompressionType": "None",
                  },
              },
          ],
          "output_config": {"Outputs": []},
          "experiment_config": None,
          "job_name": job_name,
          "resources": {
              "ClusterConfig": {
                  "InstanceType": "ml.m4.xlarge",
                  "InstanceCount": 1,
                  "VolumeSizeInGB": 30,
              }
          },
          "stopping_condition": None,
          "app_specification": {
              "ImageUri": CUSTOM_IMAGE_URI,
              "ContainerEntrypoint": [
                  "/bin/bash",
                  "/opt/ml/processing/input/entrypoint/runproc.sh",
              ],
          },
          "environment": None,
          "network_config": None,
          "role_arn": ROLE,
          "tags": None,
          "experiment_config": None,
      }
  
imports: from __future__ import absolute_import
  import copy
  import pytest
  from mock import Mock, patch, MagicMock
  from packaging import version
  from sagemaker import LocalSession
  from sagemaker.dataset_definition.inputs import S3Input, DatasetDefinition, AthenaDatasetDefinition, RedshiftDatasetDefinition
  from sagemaker.processing import ProcessingInput, ProcessingOutput, Processor, ScriptProcessor, ProcessingJob
  from sagemaker.session_settings import SessionSettings
  from sagemaker.spark.processing import PySparkProcessor
  from sagemaker.sklearn.processing import SKLearnProcessor
  from sagemaker.pytorch.processing import PyTorchProcessor
  from sagemaker.tensorflow.processing import TensorFlowProcessor
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
  from sagemaker.xgboost.processing import XGBoostProcessor
  from sagemaker.mxnet.processing import MXNetProcessor
  from sagemaker.network import NetworkConfig
  from sagemaker.processing import FeatureStoreOutput
  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 ExecutionVariables
  from tests.unit import SAGEMAKER_CONFIG_PROCESSING_JOB
label_desc: Use image node_id 40 for calling a global function with example usage: _get_expected_args_modular_code(job_name, code_s3_uri) and returns: dict