code: def __tf_flatten__(self):
      metadata = (self.mask,)
      components = (self.value,)
      return metadata, components
  
imports: import collections
  import dataclasses
  from absl.testing import parameterized
  import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.data.experimental.ops import random_access
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.data.util import nest
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the MaskedTensor obj's underlying member method code with example usage: obj.__tf_flatten__() and returns: metadata,  components