code: def _ragged_tensor_representation_as_feature_spec(
      name: str,
      tensor_representation: schema_pb2.TensorRepresentation,
      feature_by_name: Dict[str, schema_pb2.Feature],
      string_domains: Dict[str, common_types.DomainType],
  ) -> Tuple[tf.io.RaggedFeature, Optional[common_types.DomainType]]:
      """Returns a representation of a RaggedTensor as a feature spec."""
      value_feature = pop_ragged_source_columns(
          name, tensor_representation, feature_by_name
      )
      spec = tensor_representation_util.CreateTfExampleParserConfig(
          tensor_representation, value_feature.type
      )
      domain = _get_domain(value_feature, string_domains)
      return typing.cast(tf.io.RaggedFeature, spec), domain
  
imports: import dataclasses
  import typing
  from typing import Dict, List, Mapping, Optional, Tuple, Union
  import tensorflow
  from tensorflow_transform import common_types
  from tensorflow_transform.tf_metadata import schema_utils_legacy
  from tfx_bsl.tfxio import tensor_representation_util
  from tensorflow_metadata.proto.v0 import path_pb2
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 14 for calling a global function with example usage: _ragged_tensor_representation_as_feature_spec(name, tensor_representation, feature_by_name, string_domains) and returns: typing,  domain