code: def test_start_new(
      prepare_data_processing, load_config, sagemaker_session
  ):
      input_config = "input"
      output_config = "output"
      resource_config = "resource"
      load_config.return_value = {
          "input_config": input_config,
          "output_config": output_config,
          "resource_config": resource_config,
      }
  
      strategy = "MultiRecord"
      max_concurrent_transforms = 100
      max_payload = 100
      tags = [{"Key": "foo", "Value": "bar"}]
      env = {"FOO": "BAR"}
  
      transformer = Transformer(
          MODEL_NAME,
          INSTANCE_COUNT,
          INSTANCE_TYPE,
          strategy=strategy,
          output_path=OUTPUT_PATH,
          max_concurrent_transforms=max_concurrent_transforms,
          max_payload=max_payload,
          tags=tags,
          env=env,
          sagemaker_session=sagemaker_session,
      )
      transformer._current_job_name = JOB_NAME
  
      content_type = "text/csv"
      compression_type = "Gzip"
      split_type = "Line"
      io_filter = "$"
      join_source = "Input"
      model_client_config = {
          "InvocationsTimeoutInSeconds": 60,
          "InvocationsMaxRetries": 2,
      }
  
      batch_data_capture_config = BatchDataCaptureConfig(
          destination_s3_uri=OUTPUT_PATH,
          kms_key_id=KMS_KEY_ID,
          generate_inference_id=False,
      )
  
      job = _TransformJob.start_new(
          transformer=transformer,
          data=DATA,
          data_type=S3_DATA_TYPE,
          content_type=content_type,
          compression_type=compression_type,
          split_type=split_type,
          input_filter=io_filter,
          output_filter=io_filter,
          join_source=join_source,
          experiment_config={"ExperimentName": "exp"},
          model_client_config=model_client_config,
          batch_data_capture_config=batch_data_capture_config,
      )
  
      assert job.sagemaker_session == sagemaker_session
      assert job.job_name == JOB_NAME
  
      load_config.assert_called_with(
          DATA,
          S3_DATA_TYPE,
          content_type,
          compression_type,
          split_type,
          transformer,
      )
      prepare_data_processing.assert_called_with(
          io_filter, io_filter, join_source
      )
  
      sagemaker_session.transform.assert_called_with(
          job_name=JOB_NAME,
          model_name=MODEL_NAME,
          strategy=strategy,
          max_concurrent_transforms=max_concurrent_transforms,
          max_payload=max_payload,
          env=env,
          input_config=input_config,
          output_config=output_config,
          resource_config=resource_config,
          experiment_config={"ExperimentName": "exp"},
          model_client_config=model_client_config,
          tags=tags,
          data_processing=prepare_data_processing.return_value,
          batch_data_capture_config=batch_data_capture_config,
      )
  
imports: from __future__ import absolute_import
  import pytest
  from mock import MagicMock, Mock, patch, PropertyMock
  from sagemaker.session_settings import SessionSettings
  from sagemaker.transformer import _TransformJob, Transformer
  from sagemaker.workflow.pipeline_context import PipelineSession, _PipelineConfig
  from sagemaker.inputs import BatchDataCaptureConfig
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
  from tests.integ import test_local_mode
  from tests.unit import SAGEMAKER_CONFIG_TRANSFORM_JOB
label_desc: Use image node_id 26 for calling a global function with example usage: test_start_new(prepare_data_processing, load_config, sagemaker_session) without return types