code: def _get_sparse_output_annotations_v2(
      graph: tf.compat.v1.Graph, tensor_to_feature_names: Dict[str, str]
  ) -> Dict[str, List[Union[str, tf.Tensor]]]:
      annotations = _get_sparse_output_annotations(graph)
      result = {}
      for tensor, v in annotations:
          if tensor.name in tensor_to_feature_names:
              result[tensor_to_feature_names[tensor.name]] = v
      return result
  
imports: import collections
  import itertools
  from typing import Any, Callable, Dict, Iterable, List, Mapping, Optional, Tuple, Union
  from absl import logging
  import tensorflow
  from tensorflow_transform import common
  from tensorflow_transform import common_types
  from tensorflow_transform import graph_context
  from tensorflow_transform import tf2_utils
  from tensorflow_transform import tf_utils
  from tensorflow_transform.saved import saved_transform_io_v2
  from tensorflow_transform.tf_metadata import schema_utils
  from tfx_bsl.tfxio import tensor_representation_util
  from google.protobuf import any_pb2
  from tensorflow.python.eager import function
  from tensorflow.python.framework import ops
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 25 for calling a global function with example usage: _get_sparse_output_annotations_v2(graph, tensor_to_feature_names) and returns: result