class_docstr: Concrete implementation of `tf.experimental.Optional`.
  
  NOTE(mrry): This implementation is kept private, to avoid defining
  `Optional.__init__()` in the public API.
code: def get_value(self, name=None):
      # TODO(b/110122868): Consolidate the restructuring logic with similar logic
      # in `Iterator.get_next()` and `StructuredFunctionWrapper`.
      with ops.name_scope(
          name, "OptionalGetValue", [self._variant_tensor]
      ) as scope:
          with ops.colocate_with(self._variant_tensor):
              result = gen_optional_ops.optional_get_value(
                  self._variant_tensor,
                  name=scope,
                  output_types=structure.get_flat_tensor_types(
                      self._element_spec
                  ),
                  output_shapes=structure.get_flat_tensor_shapes(
                      self._element_spec
                  ),
              )
          # NOTE: We do not colocate the deserialization of composite tensors
          # because not all ops are guaranteed to have non-GPU kernels.
          return structure.from_tensor_list(self._element_spec, result)
  
imports: import abc
  from tensorflow.core.protobuf import struct_pb2
  from tensorflow.python.data.util import structure
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import type_spec
  from tensorflow.python.ops import gen_optional_ops
  from tensorflow.python.saved_model import nested_structure_coder
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 3 for calling the _OptionalImpl obj's underlying member method code with example usage: obj.get_value(name) and returns: structure