class_docstr: Model allows using pre-trained models.
class_docstr_tok: ["Model","allows","using","pre-trained","models","."]
docstr: Import model GraphDef into the current graph.
docstr_tok: ["Import","model","GraphDef","into","the","current","graph","."]
code: def import_graph(
      self,
      t_input=None,
      scope="import",
      forget_xy_shape=True,
      input_map=None,
  ):
      """Import model GraphDef into the current graph."""
      graph = tf.get_default_graph()
      assert graph.unique_name(scope, False) == scope, (
          'Scope "%s" already exists. Provide explicit scope names when '
          "importing multiple instances of the model."
      ) % scope
      t_input, t_prep_input = self.create_input(
          t_input, forget_xy_shape
      )
      final_input_map = {self.input_name: t_prep_input}
      if input_map is not None:
          final_input_map.update(input_map)
      tf.import_graph_def(self.graph_def, final_input_map, name=scope)
      self.post_import(scope)
  
      def T(layer):
          if ":" in layer:
              return graph.get_tensor_by_name("%s/%s" % (scope, layer))
          else:
              return graph.get_tensor_by_name(
                  "%s/%s:0" % (scope, layer)
              )
  
      return T
  
imports: from __future__ import absolute_import, division, print_function
  from os import path
  import warnings
  import logging
  from itertools import chain
  import tensorflow
  import numpy
  from lucid.modelzoo import util
  from lucid.modelzoo.aligned_activations import get_aligned_activations
  from lucid.modelzoo.get_activations import get_activations
  from lucid.misc.io import load, save
  import lucid.misc.io.showing
label_desc: Use image node_id 15 for calling the Model obj's underlying member method code with example usage: obj.import_graph(t_input, scope, forget_xy_shape, input_map) and returns: T, graph, graph