code: def _add_executions_into_mlmd(
      self, mlmd_artifacts: Sequence[metadata_store_pb2.Artifact]
  ):
      for mlmd_artifact in mlmd_artifacts:
          self.put_execution(
              "ProducerNode",
              inputs={},
              outputs={"x": [mlmd_artifact]},
              contexts=[self.mlmd_context],
          )
  
imports: from typing import Sequence
  import tensorflow
  from tfx import types
  from tfx.dsl.control_flow import for_each
  from tfx.dsl.input_resolution import canned_resolver_functions
  from tfx.dsl.input_resolution import resolver_op
  from tfx.dsl.input_resolution.ops import test_utils
  from tfx.orchestration import pipeline
  from tfx.orchestration.portable import inputs_utils
  from tfx.orchestration.portable.input_resolution import exceptions
  from tfx.types import channel_utils
  from tfx.types import resolved_channel
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 3 for calling the CannedResolverFunctionsTest obj's underlying member method code with example usage: obj._add_executions_into_mlmd(mlmd_artifacts) without return types