code: def get_live_output_artifacts_of_node(
      store: mlmd.MetadataStore,
      *,
      pipeline_id: str,
      node_id: str,
  ) -> Sequence[mlmd.proto.Artifact]:
      """Gets LIVE output artifacts of the given node.
  
      The function query is composed of 3 MLMD API calls:
      1. Call get_artifacts() to get LIVE artifacts attributed to the given node.
      2. Call get_executions() to get executions that created artifacts from step 1.
      3. Call get_events_by_execution_ids() and filter artifacts on whether they are
      output artifacts of executions from step 2.
  
      Args:
        store: A MetadataStore object.
        pipeline_id: A pipeline ID.
        node_id: A node ID.
  
      Returns:
        A list of output artifacts from the given node.
      """
      live_output_artifacts_of_node_by_output_key = (
          get_live_output_artifacts_of_node_by_output_key(
              store, pipeline_id=pipeline_id, node_id=node_id
          )
      )
      live_output_artifacts = list()
      for (
          nested_artifact_lists
      ) in live_output_artifacts_of_node_by_output_key.values():
          live_output_artifacts.extend(
              itertools.chain.from_iterable(nested_artifact_lists)
          )
      return live_output_artifacts
  
file_path: tfx/tfx/orchestration/portable/mlmd/store_ext.py
imports: import collections
  import itertools
  from typing import Callable, Mapping, Optional, Sequence, Union
  from tfx.dsl.compiler import compiler_utils
  from tfx.dsl.compiler import constants
  from tfx.orchestration.experimental.core import constants
  from tfx.orchestration.portable.mlmd import event_lib
  from tfx.orchestration.portable.mlmd import filter_query_builder
  import ml_metadata
label_desc: Use image node_id 6 for calling a global function with example usage: get_live_output_artifacts_of_node(store) and returns: live_output_artifacts