class_docstr: Load graphs and restore variable values from a `SavedModel`.
docstr: Run initialization ops defined in the `MetaGraphDef`.
  
  Args:
    sess: tf.compat.v1.Session to restore variable values.
    tags: a set of string tags identifying a MetaGraphDef.
    import_scope: Optional `string` -- if specified, prepend this string
      followed by '/' to all loaded tensor names. This scope is applied to
      tensor instances loaded into the passed session, but it is *not* written
      through to the static `MetaGraphDef` protocol buffer that is returned.
docstr_tok: ["Run","initialization","ops","defined","in","the","`","MetaGraphDef","`",".","Args",":","sess",":","tf.compat.v1.Session","to","restore","variable","values",".","tags",":","a","set","of","string","tags","identifying","a","MetaGraphDef",".","import_scope",":","Optional","`","string","`","--","if","specified",",","prepend","this","string","followed","by","'\/","'","to","all","loaded","tensor","names",".","This","scope","is","applied","to","tensor","instances","loaded","into","the","passed","session",",","but","it","is","*","not","*","written","through","to","the","static","`","MetaGraphDef","`","protocol","buffer","that","is","returned","."]
code: def run_init_ops(self, sess, tags, import_scope=None):
      """Run initialization ops defined in the `MetaGraphDef`.
  
      Args:
        sess: tf.compat.v1.Session to restore variable values.
        tags: a set of string tags identifying a MetaGraphDef.
        import_scope: Optional `string` -- if specified, prepend this string
          followed by '/' to all loaded tensor names. This scope is applied to
          tensor instances loaded into the passed session, but it is *not* written
          through to the static `MetaGraphDef` protocol buffer that is returned.
      """
      meta_graph_def = self.get_meta_graph_def_from_tags(tags)
      with sess.graph.as_default():
          # Get asset tensors, if any.
          asset_tensors_dictionary = get_asset_tensors(
              self._export_dir,
              meta_graph_def,
              import_scope=import_scope,
          )
  
          init_op = get_init_op(meta_graph_def, import_scope)
          if init_op is not None:
              sess.run(
                  fetches=[init_op], feed_dict=asset_tensors_dictionary
              )
  
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 8 for calling the SavedModelLoader obj's underlying member method code with example usage: obj.run_init_ops(sess, tags, import_scope) without return types