code: def load_additional_inputs(
      prefix: str,
      signature_def: tf.compat.v1.MetaGraphDef.SignatureDefEntry,
      graph: tf.Graph,
  ) -> Dict[str, types.TensorType]:
      """Loads additional input tensors from signature_def.inputs.
  
      Args:
        prefix: Prefix used for tensors in signature_def.inputs (e.g. features,
          labels, etc)
        signature_def: SignatureDef to lookup nodes in.
        graph: TensorFlow graph to lookup the nodes in.
  
      Returns:
        OrderedDict of tensors.
      """
      tensors = collections.OrderedDict()
      for k, v in extract_signature_inputs_or_outputs_with_prefix(
          prefix, signature_def.inputs, util.default_dict_key(prefix)
      ).items():
          tensors[
              k
          ] = tf.compat.v1.saved_model.utils.get_tensor_from_tensor_info(
              v, graph
          )
      return tensors
  
imports: import collections
  from typing import Dict, List, Optional, Tuple, Union
  import tensorflow
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_saved_model import constants
  from tensorflow_model_analysis.eval_saved_model import encoding
  from tensorflow_model_analysis.eval_saved_model import util
  from google.protobuf import any_pb2
  from tensorflow.core.protobuf import meta_graph_pb2
label_desc: Use image node_id 7 for calling a global function with example usage: load_additional_inputs(prefix, signature_def, graph) and returns: tensors