Downgrade some @run_v1_only annotations

Some annotations were too coarse grained, whereas others were resolved
with recent fixes.

PiperOrigin-RevId: 225455888

tensorflow/python/keras/callbacks_test.py

@@ -403,7 +403,6 @@ class KerasCallbacksTest(test.TestCase):
           float(keras.backend.get_value(
               model.optimizer.lr)) - 0.01 / 4) < keras.backend.epsilon()
 
-  @test_util.run_v1_only('b/120545219')
   def test_ReduceLROnPlateau(self):
     with self.cached_session():
       np.random.seed(1337)
@@ -675,7 +674,7 @@ class KerasCallbacksTest(test.TestCase):
       self.assertEqual(len(loss), 1)
       self.assertEqual(loss[0], np.inf)
 
-  @test_util.run_v1_only('b/120545219')
+  @test_util.run_deprecated_v1
   def test_TensorBoard(self):
     np.random.seed(1337)
 
@@ -779,7 +778,7 @@ class KerasCallbacksTest(test.TestCase):
           data_generator(True), len(x_train), epochs=2, callbacks=cbks)
       assert os.path.exists(temp_dir)
 
-  @test_util.run_v1_only('b/120545219')
+  @test_util.run_deprecated_v1
   def test_TensorBoard_multi_input_output(self):
     np.random.seed(1337)
     tmpdir = self.get_temp_dir()
@@ -851,7 +850,7 @@ class KerasCallbacksTest(test.TestCase):
                           callbacks=callbacks_factory(histogram_freq=1))
       assert os.path.isdir(filepath)
 
-  @test_util.run_v1_only('b/120545219')
+  @test_util.run_deprecated_v1
   def test_Tensorboard_histogram_summaries_in_test_function(self):
 
     class FileWriterStub(object):
@@ -929,7 +928,7 @@ class KerasCallbacksTest(test.TestCase):
 
       self.assertAllEqual(tsb.writer.steps_seen, [0, 1, 2, 3, 4, 5])
 
-  @test_util.run_v1_only('b/120545219')
+  @test_util.run_deprecated_v1
   def test_Tensorboard_histogram_summaries_with_generator(self):
     np.random.seed(1337)
     tmpdir = self.get_temp_dir()

tensorflow/python/keras/engine/sequential_test.py

@@ -226,7 +226,6 @@ class TestSequential(keras_parameterized.TestCase):
     inner_model.trainable = True
     self.assertEqual(len(model.trainable_weights), 4)
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_sequential_update_disabling(self):
     val_a = np.random.random((10, 4))
     val_out = np.random.random((10, 4))

tensorflow/python/keras/engine/training_test.py

@@ -473,7 +473,6 @@ class TrainingTest(keras_parameterized.TestCase):
         metrics=['accuracy'],
         run_eagerly=testing_utils.should_run_eagerly())
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_that_trainable_disables_updates(self):
     val_a = np.random.random((10, 4))
     val_out = np.random.random((10, 4))
@@ -1286,7 +1285,6 @@ class LossMaskingTest(keras_parameterized.TestCase):
 
 class TestDynamicTrainability(keras_parameterized.TestCase):
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_trainable_warning(self):
     with self.cached_session():
       x = np.random.random((5, 3))
@@ -1300,7 +1298,6 @@ class TestDynamicTrainability(keras_parameterized.TestCase):
       model.train_on_batch(x, y)
       self.assertRaises(Warning)
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_trainable_argument(self):
     with self.cached_session():
       x = np.random.random((5, 3))

tensorflow/python/keras/integration_test.py

@@ -35,7 +35,6 @@ class KerasIntegrationTest(test.TestCase):
   def test_version(self):
     self.assertTrue(keras.__version__.endswith('-tf'))
 
-  @test_util.run_v1_only('b/120545219')
   def test_vector_classification_sequential(self):
     with self.cached_session():
       np.random.seed(1337)
@@ -168,7 +167,6 @@ class KerasIntegrationTest(test.TestCase):
                           verbose=2)
       self.assertGreater(history.history['val_acc'][-1], 0.7)
 
-  @test_util.run_v1_only('b/120545219')
   def test_video_classification_functional(self):
     with self.cached_session():
       np.random.seed(1337)
@@ -197,7 +195,6 @@ class KerasIntegrationTest(test.TestCase):
                           verbose=2)
       self.assertGreater(history.history['val_acc'][-1], 0.7)
 
-  @test_util.run_v1_only('b/120545219')
   def test_vector_classification_shared_sequential(self):
     # Test that Sequential models that feature internal updates
     # and internal losses can be shared.
@@ -232,7 +229,6 @@ class KerasIntegrationTest(test.TestCase):
                           verbose=2)
       self.assertGreater(history.history['val_acc'][-1], 0.7)
 
-  @test_util.run_v1_only('b/120545219')
   def test_vector_classification_shared_model(self):
     # Test that functional models that feature internal updates
     # and internal losses can be shared.

tensorflow/python/keras/layers/local_test.py

@@ -235,7 +235,7 @@ class LocallyConnected2DLayersTest(test.TestCase):
 
 class LocallyConnectedImplementationModeTest(test.TestCase):
 
-  @tf_test_util.run_v1_only('b/120545219')
+  @tf_test_util.run_deprecated_v1
   def test_locallyconnected_implementation(self):
     with self.cached_session():
       num_samples = 4

tensorflow/python/keras/layers/lstm_test.py

@@ -321,7 +321,6 @@ class LSTMLayerTest(keras_parameterized.TestCase):
 
 class LSTMLayerGraphOnlyTest(test.TestCase):
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_statefulness_LSTM(self):
     num_samples = 2
     timesteps = 3

tensorflow/python/keras/layers/normalization_test.py

@@ -253,7 +253,6 @@ def _run_batchnorm_correctness_test(layer, dtype='float32', fused=False):
   np.testing.assert_allclose(out.std(), 1.0, atol=1e-1)
 
 
-@tf_test_util.run_v1_only('b/120545219')
 class NormalizationLayersGraphModeOnlyTest(test.TestCase):
 
   def test_shared_batchnorm(self):
@@ -328,6 +327,7 @@ class NormalizationLayersGraphModeOnlyTest(test.TestCase):
       x2 = model.predict(val_a)
       self.assertAllClose(x1, x2, atol=1e-7)
 
+  @tf_test_util.run_deprecated_v1
   def test_batchnorm_trainable(self):
     """Tests that batchnorm layer is trainable when learning phase is enabled.
 

tensorflow/python/keras/layers/simplernn_test.py

@@ -99,7 +99,6 @@ class SimpleRNNLayerTest(keras_parameterized.TestCase):
     self.assertEqual(layer.cell.recurrent_kernel.constraint, r_constraint)
     self.assertEqual(layer.cell.bias.constraint, b_constraint)
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_with_masking_layer_SimpleRNN(self):
     layer_class = keras.layers.SimpleRNN
     inputs = np.random.random((2, 3, 4))

tensorflow/python/keras/layers/wrappers_test.py

@@ -165,7 +165,6 @@ class TimeDistributedTest(test.TestCase):
       y = model.predict(np.random.random((10, 3, 2)))
       self.assertAllClose(np.mean(y), 0., atol=1e-1, rtol=1e-1)
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_TimeDistributed_batchnorm(self):
     with self.cached_session():
       # test that wrapped BN updates still work.
@@ -188,7 +187,6 @@ class TimeDistributedTest(test.TestCase):
       # Verify input_map has one mapping from inputs to reshaped inputs.
       self.assertEqual(len(td._input_map.keys()), 1)
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_TimeDistributed_trainable(self):
     # test layers that need learning_phase to be set
     x = keras.layers.Input(shape=(3, 2))
@@ -203,7 +201,6 @@ class TimeDistributedTest(test.TestCase):
     assert len(layer.updates) == 2
     assert len(layer.trainable_weights) == 2
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_TimeDistributed_with_masked_embedding_and_unspecified_shape(self):
     with self.cached_session():
       # test with unspecified shape and Embeddings with mask_zero
@@ -236,7 +233,6 @@ class TimeDistributedTest(test.TestCase):
         self.assertAllEqual(mask_outputs_val[i], ref_mask_val[i])
       self.assertIs(mask_outputs[-1], None)  # final layer
 
-  @tf_test_util.run_v1_only('b/120545219')
   def test_TimeDistributed_with_masking_layer(self):
     with self.cached_session():
       # test with Masking layer

tensorflow/python/keras/model_subclassing_test.py

@@ -187,7 +187,6 @@ def get_nested_model_3(input_dim, num_classes):
 
 
 @test_util.run_all_in_graph_and_eager_modes
-@test_util.run_v1_only('b/120545219')
 class ModelSubclassingTest(test.TestCase):
 
   def test_custom_build(self):
@@ -916,7 +915,6 @@ class ModelSubclassingTest(test.TestCase):
       self.assertEqual(1, len(model.get_updates_for(x)))
 
 
-@test_util.run_v1_only('b/120545219')
 class GraphSpecificModelSubclassingTests(test.TestCase):
 
   @test_util.run_deprecated_v1

tensorflow/python/kernel_tests/checkpoint_ops_test.py

@@ -230,7 +230,7 @@ class LoadAndRemapMatrixTest(test.TestCase):
           np.reshape(initializing_values, (num_rows, num_cols)),
           self.evaluate(remapped_matrix))
 
-  @test_util.run_v1_only('b/120545219')
+  @test_util.run_deprecated_v1
   def test_load_and_remap_invalid_remapping(self):
     """Tests that errors are raised when an ID maps to multiple new IDs.
 
@@ -262,7 +262,7 @@ class LoadAndRemapMatrixTest(test.TestCase):
     with self.cached_session(), self.assertRaises(errors.UnimplementedError):
       self.evaluate(remapped_matrix)
 
-  @test_util.run_v1_only('b/120545219')
+  @test_util.run_deprecated_v1
   def test_load_and_remap_incorrect_initializing_values(self):
     """Tests that errors are raised with incorrect number of init values."""
     remapped_matrix = gen_checkpoint_ops.load_and_remap_matrix(

tensorflow/python/kernel_tests/session_ops_test.py

@@ -29,9 +29,9 @@ from tensorflow.python.ops import variables
 from tensorflow.python.platform import test
 
 
-@test_util.run_v1_only("b/120545219")
 class SessionOpsTest(test.TestCase):
 
+  @test_util.run_deprecated_v1
   def testHandleBasic(self):
     with self.cached_session() as sess:
       # Return a handle.
@@ -46,6 +46,7 @@ class SessionOpsTest(test.TestCase):
       y = math_ops.multiply(x, 10)
       self.assertEqual(500, sess.run(y, feed_dict={f: h.handle}))
 
+  @test_util.run_deprecated_v1
   def testHandleEval(self):
     with self.cached_session() as sess:
       # Return a handle.
@@ -58,6 +59,7 @@ class SessionOpsTest(test.TestCase):
       # Get the tensor from its handle.
       self.assertEqual(50, h.eval())
 
+  @test_util.run_deprecated_v1
   def testHandleAndValue(self):
     with self.cached_session() as sess:
       # Return a handle and a value.
@@ -71,6 +73,7 @@ class SessionOpsTest(test.TestCase):
       self.assertEqual(50, h.eval())
       self.assertEqual(500, v)
 
+  @test_util.run_deprecated_v1
   def testHandleCond(self):
     with self.cached_session() as sess:
       # Return a handle and a value
@@ -91,6 +94,7 @@ class SessionOpsTest(test.TestCase):
 
       self.assertEqual(5000, result)
 
+  @test_util.run_deprecated_v1
   def testHandleForLoop(self):
     with self.cached_session() as sess:
       # Initialize a handle.
@@ -108,6 +112,7 @@ class SessionOpsTest(test.TestCase):
 
       self.assertEqual(100, h.eval())
 
+  @test_util.run_deprecated_v1
   def testHandleWhileLoop(self):
     with self.cached_session() as sess:
       # Initialize a handle.
@@ -128,6 +133,7 @@ class SessionOpsTest(test.TestCase):
 
       self.assertEqual(101, h.eval())
 
+  @test_util.run_deprecated_v1
   def testHandleMover(self):
     with self.cached_session() as sess:
       # Return a handle.
@@ -149,6 +155,7 @@ class SessionOpsTest(test.TestCase):
         h = self.evaluate(h)
         self.assertEqual(100, sess.run(y, feed_dict={f: h.handle}))
 
+  @test_util.run_deprecated_v1
   def testHandleDelete(self):
     with self.cached_session() as sess:
       # Return a handle.
@@ -158,6 +165,7 @@ class SessionOpsTest(test.TestCase):
       h = session_ops.get_session_handle(c)
       self.evaluate(h).delete()
 
+  @test_util.run_deprecated_v1
   def testHandleDeleteRaw(self):
     with self.cached_session() as sess:
       # Return a handle.
@@ -172,6 +180,7 @@ class SessionOpsTest(test.TestCase):
       f, x = session_ops.delete_session_tensor(raw_h)
       sess.run(x, feed_dict={f: raw_h})
 
+  @test_util.run_deprecated_v1
   def testMultiDevices(self):
     with self.cached_session() as sess:
       with ops.device(test.gpu_device_name()):
@@ -190,6 +199,7 @@ class SessionOpsTest(test.TestCase):
                      b_p: b_handle.handle})
       self.assertEqual(3.0, c_handle.eval())
 
+  @test_util.run_deprecated_v1
   def testHandleGC(self):
     with self.cached_session() as sess:
       # initial values live on CPU
@@ -214,6 +224,7 @@ class SessionOpsTest(test.TestCase):
             feed_dict={add_h1: one_handle.handle,
                        add_h2: x_handle.handle})
 
+  @test_util.run_deprecated_v1
   def testHandlePlacement(self):
     with self.cached_session() as sess:
       a = constant_op.constant(1.0)
@@ -234,7 +245,7 @@ class SessionOpsTest(test.TestCase):
                      b_p: b_handle.handle})
       self.assertEqual(3.0, c_handle.eval())
 
-  @test_util.run_v1_only("b/120545219")
+  @test_util.run_deprecated_v1
   def testFeedOneHandleDirectly(self):
     with self.cached_session() as sess:
       a = constant_op.constant(10.0)
@@ -246,7 +257,7 @@ class SessionOpsTest(test.TestCase):
 
       self.assertAllClose(2500.0, sess.run(d, feed_dict={c: h_c}))
 
-  @test_util.run_v1_only("b/120545219")
+  @test_util.run_deprecated_v1
   def testDirectHandleFeedOverlappingWithFetches(self):
     with self.cached_session() as sess:
       a = constant_op.constant(10.0)
@@ -273,6 +284,7 @@ class SessionOpsTest(test.TestCase):
       self.assertAllClose(50.0, c_val)
       self.assertAllClose(50.0, d_val)
 
+  @test_util.run_deprecated_v1
   def testFeedTwoHandlesDirectly(self):
     with self.cached_session() as sess:
       a = constant_op.constant(10.0)
@@ -287,7 +299,7 @@ class SessionOpsTest(test.TestCase):
       self.assertAllClose(48.0, sess.run(e, feed_dict={c: h_c, d: h_d}))
       self.assertAllClose(-48.0, sess.run(e, feed_dict={c: h_d, d: h_c}))
 
-  @test_util.run_v1_only("b/120545219")
+  @test_util.run_deprecated_v1
   def testFeedHandleToVariableDirectly(self):
     with self.cached_session() as sess:
       a = variables.Variable(12.0)