message: Remove run_v1_only from model_coverage Python tests.
diff: @@ -38,7 +38,6 @@ from tensorflow.python.saved_model import saved_model
  from tensorflow.python.training.training_util import write_graph
  -@test_util.run_v1_only('Incompatible with 2.0.')
  class EvaluateFrozenGraph(test.TestCase):
  def _saveFrozenGraph(self, sess):
  @@ -47,15 +46,17 @@ class EvaluateFrozenGraph(test.TestCase):
  return graph_def_file
  def testFloat(self):
  + with ops.Graph().as_default():
  with session.Session().as_default() as sess:
  in_tensor = array_ops.placeholder(
  shape=[1, 16, 16, 3], dtype=dtypes.float32)
  _ = in_tensor + in_tensor
  - filename = self._saveFrozenGraph(sess)
  + filename = self._saveFrozenGraph(sess)
  model_coverage.test_frozen_graph(filename, ['Placeholder'], ['add'])
  def testMultipleOutputs(self):
  + with ops.Graph().as_default():
  with session.Session().as_default() as sess:
  in_tensor_1 = array_ops.placeholder(
  shape=[1, 16], dtype=dtypes.float32, name='inputA')
  @@ -66,8 +67,8 @@ class EvaluateFrozenGraph(test.TestCase):
  bias = constant_op.constant(-1.0, shape=[16])
  layer = math_ops.matmul(in_tensor_1, weight) + bias
  _ = math_ops.reduce_mean(math_ops.square(layer - in_tensor_2))
  - filename = self._saveFrozenGraph(sess)
  + filename = self._saveFrozenGraph(sess)
  model_coverage.test_frozen_graph(filename, ['inputA', 'inputB'],
  ['add', 'Mean'])
  @@ -94,9 +95,10 @@ class EvaluateFrozenGraph(test.TestCase):
  def _getQuantizedModel(self):
  np.random.seed(0)
  + with ops.Graph().as_default():
  with session.Session().as_default() as sess:
  - # The tensor needs to have more than 1024 elements for quantize_weights to
  - # kick in. Thus, the [33, 33] shape.
  + # The tensor needs to have more than 1024 elements for quantize_weights
  + # to kick in. Thus, the [33, 33] shape.
  in_tensor_1 = array_ops.placeholder(
  shape=[33, 33], dtype=dtypes.float32, name='inputA')
  in_tensor_2 = constant_op.constant(
  @@ -125,11 +127,11 @@ class EvaluateFrozenGraph(test.TestCase):
  target_ops=set([lite.OpsSet.SELECT_TF_OPS]))
  -@test_util.run_v1_only('Incompatible with 2.0.')
  class EvaluateSavedModel(test.TestCase):
  def testFloat(self):
  saved_model_dir = os.path.join(self.get_temp_dir(), 'simple_savedmodel')
  + with ops.Graph().as_default():
  with session.Session().as_default() as sess:
  in_tensor_1 = array_ops.placeholder(
  shape=[1, 16, 16, 3], dtype=dtypes.float32, name='inputB')
  @@ -143,7 +145,6 @@ class EvaluateSavedModel(test.TestCase):
  model_coverage.test_saved_model(saved_model_dir)
  -@test_util.run_v1_only('Incompatible with 2.0.')
  class EvaluateKerasModel(test.TestCase):
  def _getSingleInputKerasModel(self):
  