class_docstr: Tests for the functionality of the Python wrappers.
code: def setUp(self):
      ops.reset_default_graph()
      # Create the checkpoint file in a temporary directory.
      checkpoint_prefix = os.path.join(self.get_temp_dir(), "model")
      # 0., 1., ..., 79. reshaped into [5, 16].
      initializer = init_ops.constant_initializer(
          np.reshape(np.linspace(0.0, 79, 5 * 16), (5, 16))
      )
      with self.cached_session() as sess:
          with variable_scope.variable_scope("some_scope"):
              variable_scope.get_variable(
                  name="embeddings",
                  shape=[5, 16],
                  initializer=initializer,
              )
          self.evaluate(variables.global_variables_initializer())
          saver = saver_lib.Saver()
          saver.save(sess, checkpoint_prefix, global_step=5)
      self.checkpoint_file = "{}-5".format(checkpoint_prefix)
  
      # Create the vocabulary files.
      self.new_feature_vocab_file = os.path.join(
          self.get_temp_dir(), "new_feature_vocab.txt"
      )
      with open(self.new_feature_vocab_file, "w") as f:
          f.write(
              "\n".join(["zero", "one", "two", "three", "four"]) + "\n"
          )
  
      self.old_feature_vocab_file = os.path.join(
          self.get_temp_dir(), "old_feature_vocab.txt"
      )
      with open(self.old_feature_vocab_file, "w") as f:
          f.write("\n".join(["zero", "one", "two", "three"]) + "\n")
  
      self.new_class_vocab_file = os.path.join(
          self.get_temp_dir(), "new_class_vocab.txt"
      )
      with open(self.new_class_vocab_file, "w") as f:
          f.write(
              "\n".join(["MISSING", "knitting", "flask", "eminem"])
              + "\n"
          )
  
      self.old_class_vocab_file = os.path.join(
          self.get_temp_dir(), "old_class_vocab.txt"
      )
      with open(self.old_class_vocab_file, "w") as f:
          f.write("\n".join(["knitting", "eminem", "MISSING"]) + "\n")
  
      self.init_val = 42
  
      def _init_val_initializer(shape, dtype=None, partition_info=None):
          del (
              dtype,
              partition_info,
          )  # Unused by this unit-testing initializer.
          return array_ops.tile(
              constant_op.constant(
                  [[self.init_val]], dtype=dtypes.float32
              ),
              shape,
          )
  
      self.initializer = _init_val_initializer
  
imports: import os
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import partitioned_variables
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import checkpoint_ops
  from tensorflow.python.training import saver
label_desc: Use image node_id 1 for calling the LoadAndRemapWrappersTest obj's underlying member method code with example usage: obj.setUp() and returns: array_ops