code: def test_insert_wrong_step_args_into_transform_step(
      inputs, pipeline_session
  ):
      downstream_obj, target_func_cfg = inputs
      if isinstance(downstream_obj, HyperparameterTuner):
          downstream_obj.estimator.sagemaker_session = pipeline_session
      else:
          downstream_obj.sagemaker_session = pipeline_session
      func_name = target_func_cfg["target_fun"]
      func_args = target_func_cfg["func_args"]
      step_args = getattr(downstream_obj, func_name)(**func_args)
  
      with pytest.raises(ValueError) as error:
          TransformStep(
              name="MyTransformStep",
              step_args=step_args,
          )
  
      assert (
          "The step_args of TransformStep must be obtained from transformer.transform()"
          in str(error.value)
      )
  
imports: from __future__ import absolute_import
  import json
  import pytest
  import warnings
  from copy import deepcopy
  from sagemaker import Model, Processor
  from sagemaker.estimator import Estimator
  from sagemaker.parameter import IntegerParameter
  from sagemaker.tuner import HyperparameterTuner
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
  from tests.unit.sagemaker.workflow.helpers import CustomStep, get_step_args_helper
  from sagemaker.workflow.steps import TransformStep, TransformInput
  from sagemaker.workflow.pipeline import Pipeline, PipelineGraph
  from sagemaker.workflow.parameters import ParameterString
  from sagemaker.workflow.functions import Join
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.transformer import Transformer
  from tests.unit.sagemaker.workflow.conftest import IMAGE_URI, ROLE, INSTANCE_TYPE
label_desc: Use image node_id 3 for calling a global function with example usage: test_insert_wrong_step_args_into_transform_step(inputs, pipeline_session) without return types