class_docstr: Simple wrapper of the public image models with session object.
class_docstr_tok: ["Simple","wrapper","of","the","public","image","models","with","session","object","."]
code: def import_graph(
      saved_path, endpoints, image_value_range, scope="import"
  ):
      t_input = tf.compat.v1.placeholder(
          np.float32, [None, None, None, 3]
      )
      graph = tf.Graph()
      assert graph.unique_name(scope, False) == scope, (
          'Scope "%s" already exists. Provide explicit scope names when '
          "importing multiple instances of the model."
      ) % scope
  
      graph_def = tf.compat.v1.GraphDef.FromString(
          tf.io.gfile.GFile(saved_path, "rb").read()
      )
  
      with tf.compat.v1.name_scope(scope) as sc:
          t_input, t_prep_input = PublicImageModelWrapper.create_input(
              t_input, image_value_range
          )
  
          graph_inputs = {}
          graph_inputs[endpoints["input"]] = t_prep_input
          myendpoints = tf.import_graph_def(
              graph_def, graph_inputs, list(endpoints.values()), name=sc
          )
          myendpoints = dict(
              list(zip(list(endpoints.keys()), myendpoints))
          )
          myendpoints["input"] = t_input
      return myendpoints
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from abc import ABCMeta
  from abc import abstractmethod
  from six.moves import zip
  import numpy
  import six
  import tensorflow
  from google.protobuf import text_format
label_desc: Use image node_id 6 for calling the PublicImageModelWrapper obj's underlying member method code with example usage: obj.import_graph(saved_path, endpoints, image_value_range, scope) and returns: myendpoints