diff --git a/tensorflow/lite/python/convert_saved_model_test.py b/tensorflow/lite/python/convert_saved_model_test.py
index 11bfcdc7954..fdcbc79ee9c 100644
--- a/tensorflow/lite/python/convert_saved_model_test.py
+++ b/tensorflow/lite/python/convert_saved_model_test.py
@@ -93,7 +93,7 @@ class TensorFunctionsTest(test_util.TensorFlowTestCase):
         str(error.exception))
     self.assertEqual([None, 3, 5], tensor.shape.as_list())
 
-  @test_util.run_v1_only("b/120545219")
+  @test_util.run_deprecated_v1
   def testSetTensorShapeDimensionInvalid(self):
     # Tests set_tensor_shape where the shape passed in is incompatiable.
     tensor = array_ops.placeholder(shape=[None, 3, 5], dtype=dtypes.float32)
@@ -102,9 +102,8 @@ class TensorFunctionsTest(test_util.TensorFlowTestCase):
     with self.assertRaises(ValueError) as error:
       convert_saved_model.set_tensor_shapes([tensor],
                                             {"Placeholder": [1, 5, 5]})
-    self.assertIn(
-        "The shape of tensor 'Placeholder' cannot be changed from "
-        "(?, 3, 5) to [1, 5, 5].", str(error.exception))
+    self.assertIn("The shape of tensor 'Placeholder' cannot be changed",
+                  str(error.exception))
     self.assertEqual([None, 3, 5], tensor.shape.as_list())
 
   @test_util.run_v1_only("b/120545219")
diff --git a/tensorflow/python/eager/backprop.py b/tensorflow/python/eager/backprop.py
index 29f9b2cda3a..481f680f567 100644
--- a/tensorflow/python/eager/backprop.py
+++ b/tensorflow/python/eager/backprop.py
@@ -1104,8 +1104,13 @@ class GradientTape(object):
         dimension of `target` and `source` do not match.
     """
     target_shape = target.shape
-    if not target_shape.with_rank_at_least(2)[0].is_compatible_with(
-        source.shape.with_rank_at_least(2)[0]):
+    if target_shape.rank is None:
+      dim = Dimension(None)
+    else:
+      dim = target_shape.dims[0]
+    if not (target_shape.with_rank_at_least(2) and
+            source.shape.with_rank_at_least(2) and
+            dim.is_compatible_with(source.shape[0])):
       raise ValueError(
           "Need first dimension of target shape (%s) and "
           "source shape (%s) to match." % (target.shape, source.shape))
diff --git a/tensorflow/python/eager/backprop_test.py b/tensorflow/python/eager/backprop_test.py
index 61c47a29fd2..477d18e2141 100644
--- a/tensorflow/python/eager/backprop_test.py
+++ b/tensorflow/python/eager/backprop_test.py
@@ -1338,17 +1338,14 @@ class BatchJacobianTest(test.TestCase):
                               array_ops.diag(2 * x[1] * y[1])])
     return batch_jacobian, answer
 
-  @test_util.run_v1_only('b/120545219')
   def testPfor(self):
     batch_jacobian, answer = self._batch_jacobian(experimental_use_pfor=True)
     self.assertAllEqual(answer, batch_jacobian)
 
-  @test_util.run_v1_only('b/120545219')
   def testWhileLoop(self):
     batch_jacobian, answer = self._batch_jacobian(experimental_use_pfor=False)
     self.assertAllEqual(answer, batch_jacobian)
 
-  @test_util.run_v1_only('b/120545219')
   def testPforDefun(self):
 
     @function.defun
@@ -1358,7 +1355,6 @@ class BatchJacobianTest(test.TestCase):
     batch_jacobian, answer = _f()
     self.assertAllEqual(answer, batch_jacobian)
 
-  @test_util.run_v1_only('b/120545219')
   def testWhileLoopDefun(self):
 
     @function.defun
@@ -1368,7 +1364,6 @@ class BatchJacobianTest(test.TestCase):
     batch_jacobian, answer = _f()
     self.assertAllEqual(answer, batch_jacobian)
 
-  @test_util.run_v1_only('b/120545219')
   def testPersistentTape(self):
     if not context.executing_eagerly():
       return
@@ -1379,7 +1374,6 @@ class BatchJacobianTest(test.TestCase):
     with self.assertRaisesRegexp(RuntimeError, 'persistent'):
       g.batch_jacobian(y, x, experimental_use_pfor=False)
 
-  @test_util.run_v1_only('b/120545219')
   def testBadShape(self):
     x = random_ops.random_uniform([2, 3])
     with backprop.GradientTape() as g:
@@ -1387,7 +1381,6 @@ class BatchJacobianTest(test.TestCase):
     with self.assertRaisesRegexp(ValueError, 'Need first dimension'):
       g.batch_jacobian(y, x)
 
-  @test_util.run_v1_only('b/120545219')
   def testBadInputRank(self):
     x = random_ops.random_uniform([2])
     with backprop.GradientTape() as g:
@@ -1402,7 +1395,6 @@ class BatchJacobianTest(test.TestCase):
     with self.assertRaisesRegexp(ValueError, 'must have rank at least 2'):
       g.batch_jacobian(y, x)
 
-  @test_util.run_v1_only('b/120545219')
   def testPforException(self):
     var = variables.Variable([1.])
 
@@ -1423,7 +1415,6 @@ class BatchJacobianTest(test.TestCase):
     with self.assertRaisesRegexp(ValueError, 'No converter'):
       g.batch_jacobian(y, x, experimental_use_pfor=True)
 
-  @test_util.run_v1_only('b/120545219')
   def test_parallel_iterations(self):
     with backprop.GradientTape(persistent=True) as g:
       x = constant_op.constant([[1., 2], [3, 4]])
diff --git a/tensorflow/python/eager/ops_test.py b/tensorflow/python/eager/ops_test.py
index 91d0d5c6f0f..17a090d5262 100644
--- a/tensorflow/python/eager/ops_test.py
+++ b/tensorflow/python/eager/ops_test.py
@@ -330,7 +330,6 @@ class OpsTest(test_util.TensorFlowTestCase):
     self.assertEquals(t, dtypes.string)
     self.assertEquals(r[0].dtype, dtypes.string)
 
-  @test_util.run_v1_only('b/120545219')
   def testFlattenLayer(self):
     flatten_layer = core.Flatten()
     x = constant_op.constant([[[-10, -20], [-30, -40]], [[10, 20], [30, 40]]])
diff --git a/tensorflow/python/keras/integration_test.py b/tensorflow/python/keras/integration_test.py
index c516514f632..8d65f63aba3 100644
--- a/tensorflow/python/keras/integration_test.py
+++ b/tensorflow/python/keras/integration_test.py
@@ -134,7 +134,6 @@ class KerasIntegrationTest(test.TestCase):
                           verbose=2)
       self.assertGreater(history.history['val_acc'][-1], 0.7)
 
-  @test_util.run_v1_only('b/120545219')
   def test_image_classification_sequential(self):
     with self.cached_session():
       np.random.seed(1337)
diff --git a/tensorflow/python/keras/layers/core.py b/tensorflow/python/keras/layers/core.py
index 1b406677d9f..39bcb82c720 100644
--- a/tensorflow/python/keras/layers/core.py
+++ b/tensorflow/python/keras/layers/core.py
@@ -549,8 +549,8 @@ class Flatten(Layer):
       inputs = array_ops.transpose(inputs, perm=permutation)
 
     outputs = array_ops.reshape(
-        inputs, (tensor_shape.dimension_value(inputs.shape[0])
-                 or array_ops.shape(inputs)[0], -1))
+        inputs, (tensor_shape.dimension_value(inputs.shape[0]) or
+                 array_ops.shape(inputs)[0], -1))
     if not context.executing_eagerly():
       outputs.set_shape(self.compute_output_shape(inputs.get_shape()))
     return outputs
diff --git a/tensorflow/python/keras/layers/core_test.py b/tensorflow/python/keras/layers/core_test.py
index b8def071908..f138adf7602 100644
--- a/tensorflow/python/keras/layers/core_test.py
+++ b/tensorflow/python/keras/layers/core_test.py
@@ -135,7 +135,6 @@ class CoreLayersTest(test.TestCase):
           kwargs={'dims': (1, 4, 2)}, input_shape=(3, 2, 4))
 
   @tf_test_util.run_in_graph_and_eager_modes
-  @tf_test_util.run_v1_only('b/120545219')
   def test_flatten(self):
     testing_utils.layer_test(
         keras.layers.Flatten, kwargs={}, input_shape=(3, 2, 4))
@@ -151,7 +150,6 @@ class CoreLayersTest(test.TestCase):
     self.assertAllClose(outputs, target_outputs)
 
   @tf_test_util.run_in_graph_and_eager_modes
-  @tf_test_util.run_v1_only('b/120545219')
   def test_flatten_scalar_channels(self):
     testing_utils.layer_test(
         keras.layers.Flatten, kwargs={}, input_shape=(3,))
diff --git a/tensorflow/python/kernel_tests/control_flow_ops_py_test.py b/tensorflow/python/kernel_tests/control_flow_ops_py_test.py
index 21ded25a116..f4a7d5bec90 100644
--- a/tensorflow/python/kernel_tests/control_flow_ops_py_test.py
+++ b/tensorflow/python/kernel_tests/control_flow_ops_py_test.py
@@ -1516,12 +1516,12 @@ class ControlFlowTest(test.TestCase):
         ]
 
       _, r = control_flow_ops.while_loop(c, b, [i, x])
-      self.assertEqual(r.dense_shape.get_shape()[0].value, 1)
+      self.assertEqual(r.dense_shape.get_shape()[0], 1)
 
       _, r = control_flow_ops.while_loop(
           c, b, [i, x],
           [i.get_shape(), tensor_shape.TensorShape([None])])
-      self.assertTrue(r.dense_shape.get_shape()[0].value is None)
+      self.assertEqual(r.dense_shape.get_shape().as_list(), [None])
 
       with self.assertRaisesRegexp(ValueError, "is not compatible with"):
         _, r = control_flow_ops.while_loop(
@@ -1548,15 +1548,14 @@ class ControlFlowTest(test.TestCase):
         ]
 
       _, r = control_flow_ops.while_loop(c, b, [i, x])
-      self.assertEqual(r.dense_shape.get_shape()[0].value, 2)
+      self.assertEqual(r.dense_shape.get_shape()[0], 2)
       self.assertEqual(r.values.get_shape(), tensor_shape.TensorShape([2, 2]))
 
       _, r = control_flow_ops.while_loop(
           c, b, [i, x],
           [i.get_shape(), tensor_shape.TensorShape([None, 2])])
-      self.assertEqual(r.dense_shape.get_shape()[0].value, 2)
-      self.assertTrue(r.values.get_shape()[0].value is None)
-      self.assertEqual(r.values.get_shape()[1].value, 2)
+      self.assertEqual(r.dense_shape.get_shape()[0], 2)
+      self.assertEqual(r.values.get_shape().as_list(), [None, 2])
 
       with self.assertRaisesRegexp(ValueError, "is not compatible with"):
         _, r = control_flow_ops.while_loop(
@@ -1925,7 +1924,7 @@ class ControlFlowTest(test.TestCase):
       self.assertAllClose(np.array([10.0, 10.0, 10.0]), result2)
 
   @test_util.disable_control_flow_v2("b/113324949 (RefVariable)")
-  @test_util.run_deprecated_v1
+  @test_util.run_v1_only("b/120545219")
   def testWhileUpdateVariable_3(self):
     with self.cached_session():
       select = variables.Variable([3.0, 4.0, 5.0])
diff --git a/tensorflow/python/kernel_tests/ctc_loss_op_test.py b/tensorflow/python/kernel_tests/ctc_loss_op_test.py
index 39a637d8313..352dedea4ab 100644
--- a/tensorflow/python/kernel_tests/ctc_loss_op_test.py
+++ b/tensorflow/python/kernel_tests/ctc_loss_op_test.py
@@ -242,7 +242,6 @@ class CTCLossTest(test.TestCase):
 
     self._testCTCLoss(inputs, seq_lens, labels, loss_truth, grad_truth)
 
-  @test_util.run_v1_only("b/120545219")
   def test_time_major(self):
     """Testing time_major param.
 
@@ -565,7 +564,6 @@ class CTCLossTestV2(test.TestCase):
               rtol=2e-06,
               atol=2e-06)
 
-  @test_util.run_v1_only("b/120545219")
   def testCollapseRepeated(self):
     collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
         labels=[[1, 3, 3, 3, 0],
@@ -579,7 +577,6 @@ class CTCLossTestV2(test.TestCase):
          [1, 4, 0, 0],
          [4, 2, 9, 4]])
 
-  @test_util.run_v1_only("b/120545219")
   def testCollapseRepeatedPreservesDtypes(self):
     collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
         labels=constant_op.constant(
@@ -597,7 +594,6 @@ class CTCLossTestV2(test.TestCase):
          [1, 4, 0, 0],
          [4, 2, 9, 4]])
 
-  @test_util.run_v1_only("b/120545219")
   def testCollapseRepeatedExtraPadding(self):
     collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
         labels=[[1, 3, 3, 3, 0, 0, 0],
@@ -611,7 +607,6 @@ class CTCLossTestV2(test.TestCase):
          [1, 4, 0, 0],
          [4, 2, 9, 4]])
 
-  @test_util.run_v1_only("b/120545219")
   def testCollapseRepeatedFrontRepeats(self):
     collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
         labels=[[1, 1, 1, 2, 2],
@@ -625,7 +620,6 @@ class CTCLossTestV2(test.TestCase):
          [1, 2],
          [1, 0]])
 
-  @test_util.run_v1_only("b/120545219")
   def testCollapseRepeatedAllLabelsTheSame(self):
     collapsed, new_seq_lengths = ctc_ops.collapse_repeated(
         labels=[[1, 1, 1, 1, 1],
@@ -658,7 +652,6 @@ class CTCLossTestV2(test.TestCase):
 
     self.assertAllEqual(padded_dense, new_dense)
 
-  @test_util.run_v1_only("b/120545219")
   def testUnique(self):
     labels = [
         [3, 4, 4, 3],
@@ -674,7 +667,6 @@ class CTCLossTestV2(test.TestCase):
         [0, 0, 0, 1],
     ], idx)
 
-  @test_util.run_v1_only("b/120545219")
   def testSumStates(self):
     idx = [
         [0, 1, 0, 1],
@@ -694,7 +686,6 @@ class CTCLossTestV2(test.TestCase):
          [1.8, 0.8, 0.0, 0.0]]
     ], sum_of_states)
 
-  @test_util.run_v1_only("b/120545219")
   def testStateToOlabel(self):
     labels = [
         [3, 4, 3, 4],
@@ -733,7 +724,6 @@ class CTCLossTestV2(test.TestCase):
          [22.0 + 23.0 + 24.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]],
     ])
 
-  @test_util.run_v1_only("b/120545219")
   def testStateToOlabelUnique(self):
     labels = [
         [3, 4, 3, 4],
diff --git a/tensorflow/python/kernel_tests/linalg/linear_operator_test.py b/tensorflow/python/kernel_tests/linalg/linear_operator_test.py
index 18e13a76a09..8f8b15e8ed8 100644
--- a/tensorflow/python/kernel_tests/linalg/linear_operator_test.py
+++ b/tensorflow/python/kernel_tests/linalg/linear_operator_test.py
@@ -214,7 +214,7 @@ class LinearOperatorTest(test.TestCase):
     operator = LinearOperatorMatmulSolve(matrix, is_square=True)
     self.assertTrue(operator.is_square)
 
-  @test_util.run_v1_only("b/120545219")
+  @test_util.run_deprecated_v1
   def test_linear_operator_matmul_hints_closed(self):
     matrix = array_ops.placeholder(dtypes.float32)
     operator1 = LinearOperatorMatmulSolve(matrix)
@@ -241,7 +241,7 @@ class LinearOperatorTest(test.TestCase):
     self.assertTrue(operator_matmul.is_self_adjoint)
     self.assertEqual(None, operator_matmul.is_positive_definite)
 
-  @test_util.run_v1_only("b/120545219")
+  @test_util.run_deprecated_v1
   def test_linear_operator_matmul_hints_false(self):
     matrix = array_ops.placeholder(dtypes.float32)
     operator1 = LinearOperatorMatmulSolve(
@@ -274,7 +274,7 @@ class LinearOperatorTest(test.TestCase):
     self.assertEqual(None, operator_matmul.is_self_adjoint)
     self.assertEqual(None, operator_matmul.is_positive_definite)
 
-  @test_util.run_v1_only("b/120545219")
+  @test_util.run_deprecated_v1
   def test_linear_operator_matmul_hint_infer_square(self):
     matrix1 = array_ops.placeholder(shape=[2, 3], dtype=dtypes.float32)
     matrix2 = array_ops.placeholder(shape=[3, 2], dtype=dtypes.float32)
diff --git a/tensorflow/python/layers/core_test.py b/tensorflow/python/layers/core_test.py
index 3338e55f822..b40a2682381 100644
--- a/tensorflow/python/layers/core_test.py
+++ b/tensorflow/python/layers/core_test.py
@@ -463,9 +463,9 @@ class DropoutTest(test.TestCase):
       self.assertAllClose(np.ones((5, 5)), np_output)
 
 
-@test_util.run_v1_only('b/120545219')
 class FlattenTest(test.TestCase):
 
+  @test_util.run_deprecated_v1
   def testCreateFlatten(self):
     with self.cached_session() as sess:
       x = array_ops.placeholder(shape=(None, 2, 3), dtype='float32')
@@ -490,6 +490,7 @@ class FlattenTest(test.TestCase):
     shape = core_layers.Flatten().compute_output_shape((None, 3, None))
     self.assertEqual(shape.as_list(), [None, None])
 
+  @test_util.run_deprecated_v1
   def testDataFormat5d(self):
     np_input_channels_last = np.arange(
         120, dtype='float32').reshape([1, 5, 4, 3, 2])
@@ -507,6 +508,7 @@ class FlattenTest(test.TestCase):
 
       self.assertAllEqual(np_output_cl, np_output_cf)
 
+  @test_util.run_deprecated_v1
   def testDataFormat4d(self):
     np_input_channels_last = np.arange(
         24, dtype='float32').reshape([1, 4, 3, 2])
@@ -524,11 +526,13 @@ class FlattenTest(test.TestCase):
 
       self.assertAllEqual(np_output_cl, np_output_cf)
 
+  @test_util.run_deprecated_v1
   def testFunctionalFlatten(self):
     x = array_ops.placeholder(shape=(None, 2, 3), dtype='float32')
     y = core_layers.flatten(x, name='flatten')
     self.assertEqual(y.get_shape().as_list(), [None, 6])
 
+  @test_util.run_deprecated_v1
   def testFlatten0D(self):
     x = array_ops.placeholder(shape=(None,), dtype='float32')
     y = core_layers.Flatten()(x)
@@ -537,6 +541,7 @@ class FlattenTest(test.TestCase):
     self.assertEqual(list(np_output.shape), [5, 1])
     self.assertEqual(y.shape.as_list(), [None, 1])
 
+  @test_util.run_deprecated_v1
   def testFlattenUnknownAxes(self):
     with self.cached_session() as sess:
       x = array_ops.placeholder(shape=(5, None, None), dtype='float32')
diff --git a/tensorflow/python/ops/ctc_ops.py b/tensorflow/python/ops/ctc_ops.py
index db7f9d2378c..45286f7c188 100644
--- a/tensorflow/python/ops/ctc_ops.py
+++ b/tensorflow/python/ops/ctc_ops.py
@@ -24,6 +24,7 @@ from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import function
 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
 from tensorflow.python.ops import functional_ops
@@ -1127,4 +1128,5 @@ def _scan(fn, elems, initial, reverse=False, inclusive=False, final_only=False):
 
 def _get_dim(tensor, i):
   """Get value of tensor shape[i] preferring static value if available."""
-  return tensor.shape[i].value or array_ops.shape(tensor)[i]
+  return tensor_shape.dimension_value(
+      tensor.shape[i]) or array_ops.shape(tensor)[i]
diff --git a/tensorflow/python/ops/linalg/linear_operator.py b/tensorflow/python/ops/linalg/linear_operator.py
index 8efafda3a1e..6be81f4b341 100644
--- a/tensorflow/python/ops/linalg/linear_operator.py
+++ b/tensorflow/python/ops/linalg/linear_operator.py
@@ -381,7 +381,10 @@ class LinearOperator(object):
       `Dimension` object.
     """
     # Derived classes get this "for free" once .shape is implemented.
-    return self.shape[-1]
+    if self.shape.rank is None:
+      return tensor_shape.Dimension(None)
+    else:
+      return self.shape.dims[-1]
 
   def domain_dimension_tensor(self, name="domain_dimension_tensor"):
     """Dimension (in the sense of vector spaces) of the domain of this operator.