code: def _load_transform_saved_model(transform_savedmodel_dir):
      """Load a SavedModel representing a transform function from disk.
  
      Args:
        transform_savedmodel_dir: a SavedModel directory.
  
      Returns:
        A tuple with a `MetaGraphDef` proto, the input and outputs of a
        `SignatureDef` proto, and a dict from tensor names to absolute paths for
        asset filepaths.
      """
      saved_model = saved_model_loader.parse_saved_model(
          transform_savedmodel_dir
      )
      meta_graph_def = (
          saved_model_loader.choose_meta_graph_def_and_raise(
              saved_model
          )
      )
  
      signature = meta_graph_def.signature_def[
          constants.TRANSFORM_SIGNATURE
      ]
      # The following code handles models produced prior to CL/200123875.  These
      # models used a non-standard naming convention for features in order to
      # support SparseTensor.
      # TODO(b/34253951): Remove the following code once we no longer want to
      # support the legacy formats.
      _update_legacy_signature(signature)
  
      # maps name to TensorInfo
      input_signature = signature.inputs
      output_signature = signature.outputs
  
      # asset_path_dict is {string: string}, mapping tensor names to absolute paths.
      asset_path_dict = saved_model_loader.get_asset_tensors(
          transform_savedmodel_dir, meta_graph_def
      )
  
      return (
          meta_graph_def,
          input_signature,
          output_signature,
          asset_path_dict,
      )
  
file_path: transform/tensorflow_transform/saved/saved_transform_io.py
imports: import importlib
  import os
  import re
  import tensorflow
  from tensorflow_transform.py_func import pyfunc_helper
  from tensorflow_transform.saved import constants
  from tensorflow_transform.saved import saved_model_loader
  from tensorflow.core.protobuf import struct_pb2
  from tensorflow.python.framework import ops
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.training import saver
label_desc: Use image node_id 2 for calling a global function with example usage: _load_transform_saved_model(transform_savedmodel_dir) and returns: meta_graph_def,  input_signature,  output_signature,  asset_path_dict