code: def _dtensor_distributed_value_to_tensor(
      var, dtype=None, name=None, as_ref=False
  ):
      del name
      dtensor = var.get_dtensor()
      if dtype is not None and not dtype.is_compatible_with(
          dtensor.dtype
      ):
          raise ValueError(
              "Incompatible type conversion requested to type {!r} for variable "
              "of type {!r}".format(dtype.name, dtensor.dtype.name)
          )
      if as_ref:
          raise NotImplementedError(
              "PerReplica doesn't support being used as a reference."
          )
      return dtensor
  
imports: from tensorflow.dtensor.python import accelerator_util
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import input_util
  from tensorflow.dtensor.python import layout
  from tensorflow.python.distribute import cross_device_ops
  from tensorflow.python.distribute import device_util
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import reduce_util
  from tensorflow.python.distribute import values
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion_registry
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import summary_ops_v2
label_desc: Use image node_id 1 for calling a global function with example usage: _dtensor_distributed_value_to_tensor(var, dtype, name, as_ref) and returns: dtensor