class_docstr: A replicated variable for use on TPUs.
  
  When accessed inside a tpu.replicate() context, this variable acts as if it
  is a single variable whose handle is a replicated input to the computation.
  
  Outside a tpu.replicate() context currently this object has pretty murky
  semantics, especially with respect to things such as
  * initialization
  * colocation.
  
  TODO(phawkins): merge this with the TPU DistributionStrategy code.
code: def assign_add(
      self, delta, use_locking=None, name=None, read_value=True
  ):
      del use_locking
      with _handle_graph(self.handle), self._assign_dependencies():
          assign_add_op = (
              gen_resource_variable_ops.assign_add_variable_op(
                  self.handle,
                  ops.convert_to_tensor(delta, dtype=self.dtype),
                  name=name,
              )
          )
      if read_value:
          return self._read_variable_op()
      return assign_add_op
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import contextlib
  import inspect
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion_registry
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import gen_resource_variable_ops
label_desc: Use image node_id 18 for calling the ReplicatedVariable obj's underlying member method code with example usage: obj.assign_add(delta, use_locking, name, read_value) and returns: assign_add_op, self