code: def _prepare_sample_execution_info(
      bucket, artifact_path, output_path, data_path
  ):
      """Prepare sample ImportSchemaGen execution info."""
      pipeline_root = f"gs://{bucket}"
      sample_artifact = tfx.types.standard_artifacts.Schema()
      sample_artifact.uri = pipeline_root + artifact_path
  
      execution_output_uri = pipeline_root + output_path
      stateful_working_dir = pipeline_root + "/workding/dir"
      exec_properties = {
          "schema_file": pipeline_root + data_path,
      }
      pipeline_info = pipeline_pb2.PipelineInfo(id="my_pipeline")
      pipeline_node = text_format.Parse(
          """
        node_info {
          id: 'my_node'
        }
        """,
          pipeline_pb2.PipelineNode(),
      )
  
      original = data_types.ExecutionInfo(
          input_dict={},
          output_dict={"schema": [sample_artifact]},
          exec_properties=exec_properties,
          execution_output_uri=execution_output_uri,
          stateful_working_dir=stateful_working_dir,
          pipeline_info=pipeline_info,
          pipeline_node=pipeline_node,
      )
  
      return original
  
file_path: tfx/tfx/orchestration/experimental/centralized_kubernetes_orchestrator/examples/run_sample_component.py
imports: from absl import app
  from absl import flags
  from absl import logging
  from tfx import v1
  from tfx.orchestration.experimental.centralized_kubernetes_orchestrator import kubernetes_job_runner
  from tfx.orchestration.portable import data_types
  from tfx.proto.orchestration import pipeline_pb2
  from google.protobuf import text_format
label_desc: Use image node_id 1 for calling a global function with example usage: _prepare_sample_execution_info(bucket, artifact_path, output_path, data_path) and returns: original