class_docstr: Loads a SavedModel without using Sessions.
class_docstr_tok: ["Loads","a","SavedModel","without","using","Sessions","."]
docstr: Override to support implicit one-MetaGraph loading with tags=None.
docstr_tok: ["Override","to","support","implicit","one-MetaGraph","loading","with","tags=None","."]
code: def get_meta_graph_def_from_tags(self, tags):
      """Override to support implicit one-MetaGraph loading with tags=None."""
      if tags is None:
          if len(self._saved_model.meta_graphs) != 1:
              tag_sets = [
                  mg.meta_info_def.tags
                  for mg in self._saved_model.meta_graphs
              ]
              raise ValueError(
                  "Importing a SavedModel with `tf.saved_model.load` requires a "
                  "`tags=` argument if there is more than one MetaGraph. Got "
                  f"`tags=None`, but there are {len(self._saved_model.meta_graphs)} "
                  f"MetaGraphs in the SavedModel with tag sets: {tag_sets}. Pass a "
                  "`tags=` argument to load this SavedModel."
              )
          return self._saved_model.meta_graphs[0]
      return super(
          _EagerSavedModelLoader, self
      ).get_meta_graph_def_from_tags(tags)
  
imports: import functools
  from tensorflow.python.eager import context
  from tensorflow.python.eager import lift_to_graph
  from tensorflow.python.eager import wrap_function
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import function_deserialization
  from tensorflow.python.saved_model import loader_impl
  from tensorflow.python.saved_model import signature_serialization
  from tensorflow.python.saved_model.pywrap_saved_model import metrics
  from tensorflow.python.trackable import asset
  from tensorflow.python.trackable import autotrackable
  from tensorflow.python.trackable import resource
  from tensorflow.python.training import monitored_session
  from tensorflow.python.training import saver
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling the _EagerSavedModelLoader obj's underlying member method code with example usage: obj.get_meta_graph_def_from_tags(tags) and returns: super, self