code: def translate_executor_output(
      output_dict: Mapping[str, List[artifact.Artifact]],
      name_from_id: Mapping[int, str],
  ) -> Dict[str, pipeline_pb2.ArtifactList]:
      """Translates output_dict to a Kubeflow ArtifactList mapping."""
      result = {}
      for k, v in output_dict.items():
          result[k] = pipeline_pb2.ArtifactList(
              artifacts=[
                  to_runtime_artifact(
                      artifact_utils.get_single_instance(v),
                      name_from_id,
                  )
              ]
          )
  
      return result
  
imports: import hashlib
  from typing import Any, Dict, List, Mapping, MutableMapping, Optional
  from absl import logging
  from kfp.pipeline_spec import pipeline_spec_pb2
  from tfx.components.evaluator import constants
  from tfx.orchestration.kubeflow.v2 import compiler_utils
  from tfx.types import artifact
  from tfx.types import artifact_utils
  from tfx.types import standard_component_specs
  from tfx.utils import import_utils
  import yaml
  from google.protobuf import struct_pb2
  from google.protobuf import json_format
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 6 for calling a global function with example usage: translate_executor_output(output_dict, name_from_id) and returns: result