class_docstr: Class for wrapping multiple TF 1.X functions in a single graph.
  
  Maintains a dictionary mapping names to wrapped functions. See
  `tf.compat.v1.wrap_function` to learn more about wrapping V1 functions.
  
  Functions wrapped using this class have access to variables and collections
  created in other wrapped functions, using the standard TF 1.X API (
  `tf.compat.v1.get_variable` or
  `tf.compat.v1.get_default_graph().get_collection(...)`)
  
  Outside a function, variables and collections may be accessed using the
  `variables` and `graph` properties.
  
  Example:
  
  ```
  def add_v1(x):
    with tf.compat.v1.variable_scope('vars', reuse=tf.compat.v1.AUTO_REUSE):
      v = tf.compat.v1.get_variable('v', shape=[], dtype=tf.int32)
    return v + x
  
  def increment_var_v1(x):
    with tf.compat.v1.variable_scope('vars', reuse=tf.compat.v1.AUTO_REUSE):
      v = tf.compat.v1.get_variable('v', shape=[], dtype=tf.int32)
    return v.assign_add(x)
  
  g = WrappedGraph()
  add = g.wrap_function(add_v1, [tf.TensorSpec([], tf.int32)])
  increment_var = g.wrap_function(increment_var_v1,
                                  [tf.TensorSpec([], tf.int32)])
  
  assert len(g.variables) == 1
  assert g.variables[0].numpy() == 0
  increment_var(tf.constant(5))
  assert g.variables[0].numpy() == 5
  
  ```
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code: def variables(self):
      return self._variable_holder.variables
  
imports: import weakref
  from tensorflow.core.function.polymorphism import function_type
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.core.protobuf import struct_pb2
  from tensorflow.python.eager import context
  from tensorflow.python.eager import function
  from tensorflow.python.eager import lift_to_graph
  from tensorflow.python.eager.polymorphic_function import atomic_function
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import importer
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.trackable import data_structures
  from tensorflow.python.util import nest
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 3 for calling the WrappedGraph obj's underlying member method code with example usage: obj.variables() and returns: self