class_docstr: Load graphs and restore variable values from a `SavedModel`.
docstr: Creates a `SavedModelLoader`.
  
  Args:
    export_dir: Directory in which the SavedModel protocol buffer and
      variables to be loaded are located.
docstr_tok: ["Creates","a","`","SavedModelLoader","`",".","Args",":","export_dir",":","Directory","in","which","the","SavedModel","protocol","buffer","and","variables","to","be","loaded","are","located","."]
code: def __init__(self, export_dir):
      """Creates a `SavedModelLoader`.
  
      Args:
        export_dir: Directory in which the SavedModel protocol buffer and
          variables to be loaded are located.
      """
      self._export_dir = export_dir
      self._variables_path = path_helpers.get_variables_path(export_dir)
      self._saved_model = parse_saved_model(export_dir)
  
imports: import os
  import sys
  from google.protobuf import message
  from google.protobuf import text_format
  from tensorflow.core.framework import graph_debug_info_pb2
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.core.protobuf import saved_model_pb2
  from tensorflow.python.framework import ops
  from tensorflow.python.lib.io import file_io
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import constants
  from tensorflow.python.saved_model import path_helpers
  from tensorflow.python.saved_model import signature_def_utils
  from tensorflow.python.saved_model import utils_impl
  from tensorflow.python.saved_model.pywrap_saved_model import metrics
  from tensorflow.python.training import saver
  from tensorflow.python.util import compat
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 1 to create a new SavedModelLoader object from inherited base classes: object with example: obj = SavedModelLoader(export_dir)