code: def _create_pipeline():
      pipeline_name = _PIPELINE_NAME
      pipeline_root = os.path.join(
          _get_test_output_dir(), pipeline_name
      )
      components = test_utils.create_e2e_components(
          _get_csv_input_location()
      )
      return tfx_pipeline.Pipeline(
          pipeline_name=pipeline_name,
          pipeline_root=pipeline_root,
          metadata_connection_config=metadata_store_pb2.ConnectionConfig(),
          components=components[
              :2
          ],  # Run two components only to reduce overhead.
          log_root="/var/tmp/tfx/logs",
          additional_pipeline_args={
              "WORKFLOW_ID": pipeline_name,
          },
      )
  
imports: import os
  from tfx.orchestration import pipeline
  from tfx.orchestration.kubeflow import kubeflow_dag_runner
  from tfx.tools.cli.e2e import test_utils
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 3 for calling a global function with example usage: _create_pipeline() and returns: tfx_pipeline