Remove forward_compatibility / forward_compatible checks for dates that have already passed.

- Also, removed print statements from relu_op_test.py

PiperOrigin-RevId: 287911742
Change-Id: Ib1763a5a010e5738e4d93e348391839e1e164108

tensorflow/compiler/tests/matrix_diag_ops_test.py

@@ -21,19 +21,10 @@ from __future__ import print_function
 import numpy as np
 
 from tensorflow.compiler.tests import xla_test
-from tensorflow.python.compat import compat
 from tensorflow.python.ops import array_ops
 from tensorflow.python.platform import googletest
 
 
-# LINT.IfChange
-matrix_diag_v3_forward_compat_date = (2019, 12, 6)
-# LINT.ThenChange(
-#   //tensorflow/python/kernel_tests/diag_op_test.py,
-#   //tensorflow/python/ops/array_ops.py,
-#   //tensorflow/python/ops/parallel_for/array_test.py
-# )
-
 default_v2_alignment = "LEFT_LEFT"
 alignment_list = ["RIGHT_LEFT", "LEFT_RIGHT"]
 
@@ -404,7 +395,6 @@ class MatrixDiagTest(xla_test.XLATestCase):
 
   # From here onwards are v2-only tests.
   def testSquare(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for align in alignment_list:
       for _, tests in [square_cases(align)]:
         for diag_index, (vecs, solution) in tests.items():
@@ -412,7 +402,6 @@ class MatrixDiagTest(xla_test.XLATestCase):
           self._assertOpOutputMatchesExpected(params, solution[0])
 
   def testSquareBatch(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for align in alignment_list:
       for _, tests in [square_cases(align)]:
         for diag_index, (vecs, solution) in tests.items():
@@ -420,9 +409,6 @@ class MatrixDiagTest(xla_test.XLATestCase):
           self._assertOpOutputMatchesExpected(params, solution)
 
   def testRectangularBatch(self):
-    if not compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
-      return
-
     # Stores expected num_rows and num_cols (when the other is given).
     # expected[(d_lower, d_upper)] = (expected_num_rows, expected_num_cols)
     test_list = list()
@@ -513,7 +499,6 @@ class MatrixDiagTest(xla_test.XLATestCase):
             }, solution_given_num_cols)
 
   def testPadding(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for padding_value, align in zip_to_first_list_length([555, -11],
                                                          alignment_list):
       for _, tests in all_tests(align):
@@ -634,7 +619,6 @@ class MatrixSetDiagTest(xla_test.XLATestCase):
 
   # From here onwards are v2-only tests.
   def testSingleMatrix(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for align in alignment_list:
       for _, tests in all_tests(align):
         for diag_index, (vecs, banded_mat) in tests.items():
@@ -650,7 +634,6 @@ class MatrixSetDiagTest(xla_test.XLATestCase):
               }, solution)
 
   def testBatch(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for align in alignment_list:
       for _, tests in all_tests(align):
         for diag_index, (vecs, banded_mat) in tests.items():
@@ -705,7 +688,6 @@ class MatrixDiagPartTest(xla_test.XLATestCase):
 
   # From here onwards are v2-only tests.
   def testSingleMatrix(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for align in alignment_list:
       test_list = [square_cases(align), tall_cases(align), fat_cases(align)]
       for mat, tests in test_list:
@@ -718,7 +700,6 @@ class MatrixDiagPartTest(xla_test.XLATestCase):
               }, solution[0])
 
   def testBatch(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for align in alignment_list:
       for mat, tests in all_tests(align):
         for diag_index, (solution, _) in tests.items():
@@ -730,7 +711,6 @@ class MatrixDiagPartTest(xla_test.XLATestCase):
               }, solution)
 
   def testPadding(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     for padding_value, align in zip_to_first_list_length([555, -11],
                                                          alignment_list):
       for mat, tests in all_tests(align):

tensorflow/python/data/experimental/kernel_tests/replicate_test.py

@@ -23,7 +23,6 @@ from tensorflow.core.protobuf import cluster_pb2
 from tensorflow.core.protobuf import config_pb2
 from tensorflow.core.protobuf import tensorflow_server_pb2
 from tensorflow.python import pywrap_tensorflow
-from tensorflow.python.compat import compat
 from tensorflow.python.data.experimental.ops import distribute
 from tensorflow.python.data.experimental.ops import distribute_options
 from tensorflow.python.data.kernel_tests import test_base
@@ -90,7 +89,6 @@ class LocalReplicateTest(test_base.DatasetTestBase, parameterized.TestCase):
   @combinations.generate(
       combinations.combine(tf_api_version=[1], mode=["graph", "eager"]))
   def testExternalStatePolicyIgnore(self):
-    with compat.forward_compatibility_horizon(2019, 11, 30):
     with ops.device(self._device0):
       dataset0 = dataset_ops.Dataset.range(100).map(
           lambda _: random_ops.random_uniform(  # pylint:disable=g-long-lambda
@@ -122,7 +120,6 @@ class LocalReplicateTest(test_base.DatasetTestBase, parameterized.TestCase):
   @combinations.generate(
       combinations.combine(tf_api_version=[1], mode=["graph", "eager"]))
   def testExternalStatePolicyWarn(self):
-    with compat.forward_compatibility_horizon(2019, 11, 30):
     with ops.device(self._device0):
       dataset0 = dataset_ops.Dataset.range(100).map(
           lambda _: random_ops.random_uniform(  # pylint:disable=g-long-lambda
@@ -154,7 +151,6 @@ class LocalReplicateTest(test_base.DatasetTestBase, parameterized.TestCase):
   @combinations.generate(
       combinations.combine(tf_api_version=[1], mode=["graph", "eager"]))
   def testExternalStatePolicyFail(self):
-    with compat.forward_compatibility_horizon(2019, 11, 30):
     with ops.device(self._device0):
       dataset0 = dataset_ops.Dataset.range(100).map(
           lambda _: random_ops.random_uniform(  # pylint:disable=g-long-lambda

tensorflow/python/data/experimental/ops/scan_ops.py

@@ -17,7 +17,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
 from tensorflow.python.data.util import structure
@@ -125,8 +124,7 @@ class _ScanDataset(dataset_ops.UnaryDataset):
     self._scan_func = wrapped_func
     self._scan_func.function.add_to_graph(ops.get_default_graph())
     # pylint: disable=protected-access
-    if compat.forward_compatible(2019, 10,
+    if use_default_device is not None:
-                                 15) or use_default_device is not None:
       variant_tensor = gen_experimental_dataset_ops.scan_dataset(
           self._input_dataset._variant_tensor,
           structure.to_tensor_list(self._state_structure, self._initial_state),

tensorflow/python/data/kernel_tests/iterator_test.py

@@ -25,7 +25,6 @@ import numpy as np
 from tensorflow.core.protobuf import cluster_pb2
 from tensorflow.core.protobuf import config_pb2
 from tensorflow.python.client import session
-from tensorflow.python.compat import compat as forward_compat
 from tensorflow.python.data.kernel_tests import test_base
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.ops import iterator_ops
@@ -464,7 +463,6 @@ class IteratorTest(test_base.DatasetTestBase, parameterized.TestCase):
 
   @combinations.generate(test_base.graph_only_combinations())
   def testIteratorStringHandleFuture(self):
-    with forward_compat.forward_compatibility_horizon(2018, 8, 4):
     dataset_3 = dataset_ops.Dataset.from_tensor_slices([1, 2, 3])
     dataset_4 = dataset_ops.Dataset.from_tensor_slices([10, 20, 30, 40])
 

tensorflow/python/data/ops/dataset_ops.py

@@ -30,7 +30,6 @@ from six.moves import queue as Queue  # pylint: disable=redefined-builtin
 
 from tensorflow.core.framework import graph_pb2
 from tensorflow.python import tf2
-from tensorflow.python.compat import compat
 from tensorflow.python.data.experimental.ops import distribute_options
 from tensorflow.python.data.experimental.ops import optimization_options
 from tensorflow.python.data.experimental.ops import stats_options
@@ -223,7 +222,7 @@ class DatasetV2(tracking_base.Trackable, composite_tensor.CompositeTensor):
       A scalar `tf.Tensor` of `tf.string` type, representing this dataset as a
       serialized graph.
     """
-    if compat.forward_compatible(2019, 11, 25) or external_state_policy:
+    if external_state_policy:
       policy = None
       if external_state_policy:
         policy = external_state_policy.value
@@ -231,7 +230,7 @@ class DatasetV2(tracking_base.Trackable, composite_tensor.CompositeTensor):
           self._variant_tensor,
           external_state_policy=policy,
           strip_device_assignment=strip_device_assignment)
-    if compat.forward_compatible(2019, 11, 16) or strip_device_assignment:
+    if strip_device_assignment:
       return gen_dataset_ops.dataset_to_graph(
           self._variant_tensor,
           allow_stateful=allow_stateful,

tensorflow/python/grappler/auto_mixed_precision_test.py

@@ -28,7 +28,6 @@ from tensorflow.core.protobuf import config_pb2
 from tensorflow.core.protobuf import rewriter_config_pb2
 from tensorflow.python import tf2
 from tensorflow.python.client import session
-from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
@@ -395,7 +394,6 @@ class AutoMixedPrecisionTest(test.TestCase):
   @test_util.disable_xla('This test does not pass with XLA')
   def test_conv_bn(self):
     """Test graph with convolution followed by batch norm."""
-    with compat.forward_compatibility_horizon(2019, 6, 7):
     if test.is_gpu_available(cuda_only=True):
       random_seed.set_random_seed(0)
       x = _input([2, 8, 8, 1])
@@ -468,7 +466,6 @@ class AutoMixedPrecisionTest(test.TestCase):
   @test_util.disable_xla('This test does not pass with XLA')
   def test_conv_bn_dropout(self):
     """Test dropout precision of convolution batch norm graph."""
-    with compat.forward_compatibility_horizon(2019, 6, 7):
     if test.is_gpu_available(cuda_only=True):
       random_seed.set_random_seed(0)
       x = _input([2, 8, 8, 1])

tensorflow/python/kernel_tests/batch_matmul_op_test.py

@@ -22,7 +22,6 @@ import numpy as np
 
 from tensorflow.python import tf2
 from tensorflow.python.client import session
-from tensorflow.python.compat import compat
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
@@ -143,7 +142,6 @@ def _GetBatchMatmulOpBroadcastingTest(dtype, adjoint_a, adjoint_b,
                                       use_static_shape):
 
   def Test(self):
-    with compat.forward_compatibility_horizon(2019, 4, 26):
     np.random.seed(42)
     self._testBroadcasting(dtype, adjoint_a, adjoint_b, use_static_shape)
 
@@ -200,7 +198,6 @@ def _GetBatchMatmulGradientWithBroadcastingTest(dtype, adjoint_a, adjoint_b):
     def CheckGradients(self, a_shape, b_shape):
       self._compare(a_shape, b_shape, dtype, adjoint_a, adjoint_b)
 
-    with compat.forward_compatibility_horizon(2019, 4, 26):
     CheckGradients(self, [1, 5, 2, 3], [7, 1, 3, 2])
     CheckGradients(self, [2, 3], [1, 3, 5])
     CheckGradients(self, [2, 3], [5, 3, 5])
@@ -231,7 +228,6 @@ class BatchMatMulBenchmark(test.Benchmark):
 
   def benchmarkBatchMatMulBroadcast(self):
     for (a_shape, b_shape) in self.shape_pairs:
-      with compat.forward_compatibility_horizon(2019, 4, 26):
       with ops.Graph().as_default(), \
           session.Session(config=benchmark.benchmark_config()) as sess, \
           ops.device("/cpu:0"):

tensorflow/python/kernel_tests/diag_op_test.py

@@ -21,7 +21,6 @@ import itertools
 
 import numpy as np
 
-from tensorflow.python.compat import compat
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes as dtypes_lib
 from tensorflow.python.framework import ops
@@ -33,15 +32,6 @@ from tensorflow.python.platform import test
 from tensorflow.python.platform import tf_logging
 
 
-# LINT.IfChange
-matrix_diag_v3_forward_compat_date = (2019, 12, 6)
-# LINT.ThenChange(
-#   //tensorflow/compiler/tests/matrix_diag_ops_test.py,
-#   //tensorflow/python/ops/array_ops.py,
-#   //tensorflow/python/ops/parallel_for/array_test.py
-# )
-
-
 default_v2_alignment = "LEFT_LEFT"
 alignment_list = ["RIGHT_LEFT", "LEFT_RIGHT", "LEFT_LEFT", "RIGHT_RIGHT"]
 
@@ -391,7 +381,6 @@ class MatrixDiagTest(test.TestCase):
       self.assertEqual((3, 3), v_diag.get_shape())
       self.assertAllEqual(v_diag.eval(), mat)
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # {Sub,Super}diagonals.
       for offset in [1, -2, 5]:
         mat = np.diag(v, offset)
@@ -417,7 +406,6 @@ class MatrixDiagTest(test.TestCase):
       self.assertEqual((2, 3, 3), v_batch_diag.get_shape())
       self.assertAllEqual(v_batch_diag.eval(), mat_batch)
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # {Sub,Super}diagonals.
       for offset in [1, -2, 5]:
         v_batch_diag = array_ops.matrix_diag(v_batch, k=offset)
@@ -453,7 +441,6 @@ class MatrixDiagTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testRectangularBatch(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     with self.cached_session(use_gpu=True):
       # Stores expected num_rows and num_cols (when the other is given).
       # expected[d_lower, d_upper] = (expected_num_rows, expected_num_cols)
@@ -574,7 +561,6 @@ class MatrixDiagTest(test.TestCase):
                                                         y.get_shape().as_list())
         self.assertLess(error, 1e-4)
 
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     # {Sub,super}diagonals/band.
     tests = dict()  # tests[shape] = (d_lower, d_upper)
     tests[(3,)] = (-1, -1)
@@ -604,7 +590,6 @@ class MatrixSetDiagTest(test.TestCase):
       self.assertEqual((3, 3), output.get_shape())
       self.assertAllEqual(mat_set_diag, self.evaluate(output))
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # Diagonal bands.
       for align in alignment_list:
         _, tests = square_cases(align)
@@ -634,7 +619,6 @@ class MatrixSetDiagTest(test.TestCase):
       self.assertEqual((3, 2), output.get_shape())
       self.assertAllEqual(expected, self.evaluate(output))
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # Diagonal bands.
       for align in alignment_list:
         for _, tests in [tall_cases(align), fat_cases(align)]:
@@ -663,7 +647,6 @@ class MatrixSetDiagTest(test.TestCase):
       self.assertEqual((2, 3, 3), output.get_shape())
       self.assertAllEqual(mat_set_diag_batch, self.evaluate(output))
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # Diagonal bands.
       for align in alignment_list:
         _, tests = square_cases(align)
@@ -697,7 +680,6 @@ class MatrixSetDiagTest(test.TestCase):
       self.assertEqual((2, 2, 3), output.get_shape())
       self.assertAllEqual(mat_set_diag_batch, self.evaluate(output))
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # Diagonal bands.
       for align in alignment_list:
         for _, tests in [tall_cases(align), fat_cases(align)]:
@@ -727,7 +709,6 @@ class MatrixSetDiagTest(test.TestCase):
       with self.assertRaisesOpError("diagonal must be at least 1-dim"):
         array_ops.matrix_set_diag([[v]], v).eval(feed_dict={v: 0.0})
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       d = array_ops.placeholder(dtype=dtypes_lib.float32)
       with self.assertRaisesOpError(
           "first dimensions of diagonal don't match"):
@@ -743,10 +724,7 @@ class MatrixSetDiagTest(test.TestCase):
       x_diag = constant_op.constant(
           np.random.rand(*diag_shape), dtype=dtypes_lib.float32)
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       y = array_ops.matrix_set_diag(x, x_diag, k=diags, align=align)
-      else:
-        y = array_ops.matrix_set_diag(x, x_diag)
       error_x = gradient_checker.compute_gradient_error(x,
                                                         x.get_shape().as_list(),
                                                         y,
@@ -763,7 +741,6 @@ class MatrixSetDiagTest(test.TestCase):
     input_shapes = [(3, 4, 4), (3, 3, 4), (3, 4, 3), (7, 4, 8, 8)]
     diag_bands = [(0, 0)]
 
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     diag_bands.append((-1, 1))
     for input_shape, diags, align in itertools.product(input_shapes, diag_bands,
                                                        alignment_list):
@@ -805,7 +782,6 @@ class MatrixDiagPartTest(test.TestCase):
       self.assertEqual((3,), mat_diag.get_shape())
       self.assertAllEqual(mat_diag.eval(), v)
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       for offset in [-2, 3]:
         mat = np.diag(v, offset)
         mat_diag = array_ops.matrix_diag_part(mat, k=offset)
@@ -831,7 +807,6 @@ class MatrixDiagPartTest(test.TestCase):
       mat_diag = array_ops.matrix_diag_part(mat)
       self.assertAllEqual(mat_diag.eval(), np.array([1.0, 4.0]))
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # Diagonal bands.
       for align in alignment_list:
         for mat, tests in [tall_cases(align), fat_cases(align)]:
@@ -853,7 +828,6 @@ class MatrixDiagPartTest(test.TestCase):
       self.assertEqual((2, 3), mat_batch_diag.get_shape())
       self.assertAllEqual(mat_batch_diag.eval(), v_batch)
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # Diagonal bands with padding_value.
       for padding_value, align in zip_to_first_list_length([0, 555, -11],
                                                            alignment_list):
@@ -889,7 +863,6 @@ class MatrixDiagPartTest(test.TestCase):
       self.assertEqual((2, 2), mat_batch_diag.get_shape())
       self.assertAllEqual(mat_batch_diag.eval(), v_batch)
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       # Diagonal bands with padding_value and align.
       for padding_value, align in zip_to_first_list_length([0, 555, -11],
                                                            alignment_list):
@@ -905,7 +878,6 @@ class MatrixDiagPartTest(test.TestCase):
 
   @test_util.run_deprecated_v1
   def testUnknownShape(self):
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     matrix = array_ops.placeholder(dtypes_lib.int32, shape=[None, None])
     result = array_ops.matrix_diag_part(matrix, k=-1)
     input_matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
@@ -939,7 +911,6 @@ class MatrixDiagPartTest(test.TestCase):
                                                         y.get_shape().as_list())
         self.assertLess(error, 1e-4)
 
-    if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
     # {Sub,super}diagonals/band.
     tests = dict()  # tests[shape] = (d_lower, d_upper)
     tests[(3, 3)] = (-1, -1)

tensorflow/python/kernel_tests/relu_op_test.py

@@ -22,7 +22,6 @@ import numpy as np
 from six.moves import xrange  # pylint: disable=redefined-builtin
 
 from tensorflow.python import tf2
-from tensorflow.python.compat import compat
 from tensorflow.python.eager import backprop
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
@@ -122,7 +121,6 @@ class ReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.relu, [x]))
-    print("relu (float32) gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   # The gradient for fp16 is inaccurate due to the low-precision.
@@ -171,7 +169,6 @@ class ReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.relu, [x]))
-    print("relu (float64) gradient err = ", err)
     self.assertLess(err, 1e-10)
 
   def testGradGradFloat32(self):
@@ -190,7 +187,6 @@ class ReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-    print("relu (float32) gradient of gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradGradFloat64(self):
@@ -209,7 +205,6 @@ class ReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-    print("relu (float64) gradient of gradient err = ", err)
     self.assertLess(err, 1e-10)
 
   def testGradientScalar(self):
@@ -283,7 +278,6 @@ class Relu6Test(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.relu6, [x]))
-    print("relu6 (float32) gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradientFloat64(self):
@@ -294,7 +288,6 @@ class Relu6Test(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.relu6, [x]))
-    print("relu6 (float64) gradient err = ", err)
     self.assertLess(err, 1e-10)
 
 
@@ -345,7 +338,6 @@ class LeakyReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.leaky_relu, [x]))
-    print("leaky_relu (float32) gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradientFloat64(self):
@@ -356,11 +348,9 @@ class LeakyReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.leaky_relu, [x]))
-    print("leaky_relu (float64) gradient err = ", err)
     self.assertLess(err, 1e-10)
 
   def testGradGradFloat32(self):
-    with compat.forward_compatibility_horizon(2018, 11, 2):
     with self.cached_session():
 
       def f(x):
@@ -376,11 +366,9 @@ class LeakyReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-      print("leaky_relu (float32) gradient of gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradGradFloat64(self):
-    with compat.forward_compatibility_horizon(2018, 11, 2):
     with self.cached_session():
 
       def f(x):
@@ -396,7 +384,6 @@ class LeakyReluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-      print("leaky_relu (float64) gradient of gradient err = ", err)
     self.assertLess(err, 1e-10)
 
   def testGradientScalar(self):
@@ -463,7 +450,6 @@ class EluTest(test.TestCase):
       x = np.asarray(x_val, dtype=np.float32, order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.elu, [x]))
-    print("elu (float32) gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradientFloat64(self):
@@ -472,7 +458,6 @@ class EluTest(test.TestCase):
       x = np.asarray(x_val, dtype=np.float64, order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.elu, [x]))
-    print("elu (float64) gradient err = ", err)
     self.assertLess(err, 1e-6)
 
   def testGradGrad(self):
@@ -507,7 +492,6 @@ class EluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-    print("elu (float32) gradient of gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradGradFloat64(self):
@@ -526,7 +510,6 @@ class EluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-    print("elu (float64) gradient of gradient err = ", err)
     self.assertLess(err, 1e-6)
 
 
@@ -567,7 +550,6 @@ class SeluTest(test.TestCase):
       x = np.asarray(x_val, dtype=np.float32, order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.selu, [x]))
-    print("selu (float32) gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradientFloat64(self):
@@ -576,7 +558,6 @@ class SeluTest(test.TestCase):
       x = np.asarray(x_val, dtype=np.float64, order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(nn_ops.selu, [x]))
-    print("selu (float64) gradient err = ", err)
     self.assertLess(err, 1e-6)
 
   def testGradGradFloat32(self):
@@ -595,7 +576,6 @@ class SeluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-    print("selu (float32) gradient of gradient err = ", err)
     self.assertLess(err, 1e-4)
 
   def testGradGradFloat64(self):
@@ -614,7 +594,6 @@ class SeluTest(test.TestCase):
           order="F")
       err = gradient_checker_v2.max_error(
           *gradient_checker_v2.compute_gradient(f, [x]))
-    print("selu (float64) gradient of gradient err = ", err)
     self.assertLess(err, 1e-6)
 
 

tensorflow/python/ops/array_ops.py

@@ -22,7 +22,6 @@ from __future__ import print_function
 import numpy as np
 import six
 
-from tensorflow.python.compat import compat
 from tensorflow.python.eager import context
 from tensorflow.python.framework import common_shapes
 from tensorflow.python.framework import composite_tensor
@@ -54,13 +53,6 @@ tf_export("newaxis").export_constant(__name__, "newaxis")
 # existing 'slice' for later use in this module.
 _BaseSlice = slice
 
-# LINT.IfChange
-matrix_diag_v3_forward_compat_date = (2019, 12, 6)
-# LINT.ThenChange(
-#   //tensorflow/compiler/tests/matrix_diag_ops_test.py,
-#   //tensorflow/python/kernel_tests/diag_op_test.py,
-#   //tensorflow/python/ops/parallel_for/array_test.py
-# )
 
 @tf_export("reshape", v1=["reshape", "manip.reshape"])
 def reshape(tensor, shape, name=None):  # pylint: disable=redefined-outer-name
@@ -2362,7 +2354,6 @@ def matrix_diag(diagonal,
   Returns:
     A Tensor. Has the same type as `diagonal`.
   """
-  if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
   # Special case to sidestep the tf.constant conversion error:
   # TypeError: Expected bool, got 0 of type 'int' instead.
   if hasattr(diagonal, "dtype") and diagonal.dtype == "bool":
@@ -2377,10 +2368,6 @@ def matrix_diag(diagonal,
       align=align,
       name=name)
 
-  # Call v1 to maintain forward compatibility.
-  # (We skip v2 because its alignment conflicts with v3's default alignment.)
-  return gen_array_ops.matrix_diag(diagonal=diagonal, name=name)
-
 
 @tf_export("linalg.diag_part", v1=["linalg.diag_part", "matrix_diag_part"])
 @deprecation.deprecated_endpoints("matrix_diag_part")
@@ -2513,7 +2500,6 @@ def matrix_diag_part(
   Returns:
     A Tensor containing diagonals of `input`. Has the same type as `input`.
   """
-  if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
   # Special case to sidestep the tf.constant conversion error:
   # TypeError: Expected bool, got 0 of type 'int' instead.
   if hasattr(input, "dtype") and input.dtype == "bool":
@@ -2522,10 +2508,6 @@ def matrix_diag_part(
   return gen_array_ops.matrix_diag_part_v3(
       input=input, k=k, padding_value=padding_value, align=align, name=name)
 
-  # Call v1 to maintain forward compatibility.
-  # (We skip v2 because its alignment conflicts with v3's default alignment.)
-  return gen_array_ops.matrix_diag_part(input=input, name=name)
-
 
 @tf_export("linalg.set_diag", v1=["linalg.set_diag", "matrix_set_diag"])
 @deprecation.deprecated_endpoints("matrix_set_diag")
@@ -2659,15 +2641,9 @@ def matrix_set_diag(
       the left (right-pads the row). It is the packing format LAPACK uses.
       cuSPARSE uses "LEFT_RIGHT", which is the opposite alignment.
   """
-  if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
   return gen_array_ops.matrix_set_diag_v3(
       input=input, diagonal=diagonal, k=k, align=align, name=name)
 
-  # Call v1 to maintain forward compatibility.
-  # (We skip v2 because its alignment conflicts with v3's default alignment.)
-  return gen_array_ops.matrix_set_diag(
-      input=input, diagonal=diagonal, name=name)
-
 
 # pylint: enable=invalid-name
 
@@ -4921,7 +4897,7 @@ def quantize_v2(
       raise ValueError("input should have known rank to use negative axis.")
     axis %= input.shape.ndims
 
-  if compat.forward_compatible(2019, 11, 13) or ensure_minimum_range != 0.01:
+  if ensure_minimum_range != 0.01:
     return gen_array_ops.quantize_v2(
         input,
         min_range,
@@ -4965,7 +4941,7 @@ def quantize(
     axis=None,
     ensure_minimum_range=0.01):
   """Quantize the input tensor."""
-  if compat.forward_compatible(2019, 11, 13) or ensure_minimum_range != 0.01:
+  if ensure_minimum_range != 0.01:
     return quantize_v2(
         input,
         min_range,
@@ -5007,7 +4983,7 @@ def dequantize(  # pylint: disable=missing-docstring
       raise ValueError("input should have known rank to use negative axis.")
     axis %= input.shape.ndims
 
-  if compat.forward_compatible(2019, 10, 22) or axis >= 0 or narrow_range:
+  if axis >= 0 or narrow_range:
     return gen_array_ops.dequantize(
         input, min_range, max_range, mode=mode, name=name,
         narrow_range=narrow_range, axis=axis)

tensorflow/python/ops/nn_fused_batchnorm_test.py

@@ -20,7 +20,6 @@ from __future__ import print_function
 
 import numpy as np
 
-from tensorflow.python.compat import compat
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import test_util
@@ -383,7 +382,6 @@ class BatchNormalizationTest(test.TestCase):
           x_shape, dtype, [6], np.float32, use_gpu=False, data_format='NHWC')
 
   def testInferenceShape5(self):
-    with compat.forward_compatibility_horizon(2019, 6, 7):
     x_shape = [0, 131, 127, 6]
     for dtype in [np.float16, np.float32]:
       if test.is_gpu_available(cuda_only=True):
@@ -450,7 +448,6 @@ class BatchNormalizationTest(test.TestCase):
 
   @test_util.disable_xla('b/141236973: Empty inputs wrong on CPU.')
   def testTrainingShape5(self):
-    with compat.forward_compatibility_horizon(2019, 6, 7):
     x_shape = [0, 131, 127, 6]
     for dtype in [np.float16, np.float32]:
       if test.is_gpu_available(cuda_only=True):
@@ -586,7 +583,6 @@ class BatchNormalizationTest(test.TestCase):
   @test_util.run_deprecated_v1
   @test_util.disable_xla('This test never passed for XLA')
   def testBatchNormGradShape5(self):
-    with compat.forward_compatibility_horizon(2019, 6, 7):
     for is_training in [True, False]:
       x_shape = [0, 7, 11, 4]
       for dtype in [np.float16, np.float32]:

tensorflow/python/ops/parallel_for/array_test.py

@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-from tensorflow.python.compat import compat
 from tensorflow.python.eager import backprop
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
@@ -33,15 +32,6 @@ from tensorflow.python.ops.parallel_for.test_util import PForTestCase
 from tensorflow.python.platform import test
 
 
-# LINT.IfChange
-matrix_diag_v3_forward_compat_date = (2019, 12, 6)
-# LINT.ThenChange(
-#   //tensorflow/compiler/tests/matrix_diag_ops_test.py,
-#   //tensorflow/python/kernel_tests/diag_op_test.py,
-#   //tensorflow/python/ops/array_ops.py
-# )
-
-
 @test_util.run_all_in_graph_and_eager_modes
 class ArrayTest(PForTestCase):
 
@@ -345,10 +335,8 @@ class ArrayTest(PForTestCase):
 
     def loop_fn(i):
       diagonal = array_ops.gather(x, i)
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       return array_ops.matrix_diag(
           diagonal, k=(0, 1), num_rows=4, num_cols=5, align="RIGHT_LEFT")
-      return array_ops.matrix_diag(diagonal)
 
     self._test_loop_fn(loop_fn, 3)
 
@@ -357,10 +345,8 @@ class ArrayTest(PForTestCase):
 
     def loop_fn(i):
       input = array_ops.gather(x, i)  # pylint: disable=redefined-builtin
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       return array_ops.matrix_diag_part(
           input, k=(-2, 0), padding_value=3, align="RIGHT_LEFT")
-      return array_ops.matrix_diag_part(input)
 
     self._test_loop_fn(loop_fn, 3)
 
@@ -378,7 +364,6 @@ class ArrayTest(PForTestCase):
           array_ops.matrix_set_diag(matrix_i, diags[0, ...]),
       ]
 
-      if compat.forward_compatible(*matrix_diag_v3_forward_compat_date):
       k = (-1, 1)
       band_i = array_ops.gather(bands, i)
       for align in ["RIGHT_LEFT", "LEFT_RIGHT"]:

tensorflow/python/ops/parallel_for/control_flow_ops_test.py

@@ -28,7 +28,6 @@ import numpy as np
 from tensorflow.core.example import example_pb2
 from tensorflow.core.example import feature_pb2
 from tensorflow.python.client import session
-from tensorflow.python.compat import compat
 from tensorflow.python.eager import backprop
 from tensorflow.python.eager import def_function
 from tensorflow.python.framework import constant_op
@@ -444,7 +443,6 @@ class NNTest(PForTestCase):
     self._test_loop_fn(loop_fn, 3)
 
   def test_fused_batch_norm(self):
-    with compat.forward_compatibility_horizon(2019, 6, 7):
     data_formats = ["NHWC"]
     if test.is_gpu_available():
       data_formats.append("NCHW")

tensorflow/python/ops/special_math_ops.py

@@ -33,7 +33,6 @@ import six
 from six.moves import xrange  # pylint: disable=redefined-builtin
 
 from tensorflow.compiler.tf2xla.ops import gen_xla_ops
-from tensorflow.python.compat import compat as fwd_compat
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import tensor_shape
 from tensorflow.python.ops import array_ops
@@ -253,10 +252,7 @@ def einsum(equation, *inputs, **kwargs):
       - the format of `equation` is incorrect,
       - number of inputs or their shapes are inconsistent with `equation`.
   """
-  if fwd_compat.forward_compatible(2019, 10, 18):
   return _einsum_v2(equation, *inputs, **kwargs)
-  else:
-    return _einsum_v1(equation, *inputs, **kwargs)
 
 
 def _einsum_v1(equation, *inputs, **kwargs):

tensorflow/python/ops/special_math_ops_test.py

@@ -23,7 +23,6 @@ import opt_einsum
 import six
 
 from tensorflow.python.client import session
-from tensorflow.python.compat import compat
 from tensorflow.python.eager import context
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
@@ -243,7 +242,6 @@ class EinsumTest(test.TestCase):
     self._check('abc->ca', (3, 4, 5))
     self._check('abc->cab', (3, 4, 5))
 
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # Empty cases.
     self._check('', ())
     self._check('->', ())
@@ -266,7 +264,6 @@ class EinsumTest(test.TestCase):
     self._check('...ij->...ji', (5, 2, 3))  # batch matrix transpose
     self._check('...ij->...', (5, 2, 3))  # batch sum
 
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     self._check('...->...', ())
     self._check('->...', ())
 
@@ -301,7 +298,6 @@ class EinsumTest(test.TestCase):
     self._check('ab,ab->', (3, 4), (3, 4))
 
   def test_repeated_indices(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # Repeated indices.
     self._check('ijj,k->ik', (2, 3, 3), (4,))
     self._check('aba,a->b', (3, 4, 3), (3,))
@@ -324,7 +320,6 @@ class EinsumTest(test.TestCase):
     self._check('...i,...j->...ij', (5, 2), (5, 3))  # outer product
 
   def test_broadcasting(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # Batch matmul with broadcasting.
     self._check('...ij,...jk->...ik', (1, 2, 3), (3, 5))
     self._check('...ij,...jk->...ik', (2, 3), (1, 3, 5))
@@ -388,12 +383,10 @@ class EinsumTest(test.TestCase):
           ((4, 3), (None, 3)))
 
     # Ellipsis with unknown rank.
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     check('bijl,bjkm->bik', ((9, 2, 3, 5), None), ((9, 3, 4, 7), None))
     check('...ij,...jk->...ik', ((3, 1, 2, 3), None), ((1, 7, 3, 4), None))
 
   def test_numpy_input(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # In addition to Tensors, we also support raw numpy arrays as inputs.
     r = np.random.RandomState(0)
     s = 'ijk,ijl,ikl->i'
@@ -464,7 +457,6 @@ class EinsumTest(test.TestCase):
 
   @test_util.disable_xla('b/131919749')
   def test_long_cases_with_repeated_labels(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     cases = [
         # Tests from dask.
         'fdf,cdd,ccd,afe->ae',
@@ -481,7 +473,6 @@ class EinsumTest(test.TestCase):
   @test_util.disable_xla('b/131919749')
   @test_util.run_in_graph_and_eager_modes
   def test_invalid_equation(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     r = np.random.RandomState(0)
     cases = [
         # invalid equation format.
@@ -535,7 +526,6 @@ class EinsumTest(test.TestCase):
     # From transformer xl.
     check('ibnd,ijbn->jnd', [(1, 0, 5, 10), (1, 1, 0, 5)], (1, 5, 10))
 
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # Generalized traces with zero-sized dimensions.
     check('aab,bc->ac', [(0, 0, 10), (10, 10)], (0, 10))
     check('aaab,bc->c', [(0, 0, 0, 3), (3, 4)], (4,))
@@ -556,7 +546,6 @@ class EinsumGradTest(test.TestCase):
 
   @test_util.disable_xla('b/131919749')
   def test_unary(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     self._check_gradient('->', ())
     self._check_gradient('aaa->a', (3, 3, 3))
     self._check_gradient('aabcd->ad', (3, 3, 5, 4, 4))
@@ -564,7 +553,6 @@ class EinsumGradTest(test.TestCase):
 
   @test_util.disable_xla('b/131919749')
   def test_unary_ellipsis(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     self._check_gradient('...->...', ())
     self._check_gradient('...->', ())
     self._check_gradient('->...', ())
@@ -582,7 +570,6 @@ class EinsumGradTest(test.TestCase):
     self._check_gradient('ab...cd->da...', (3, 5, 2, 3, 4, 2))
 
   def test_binary_simple(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # Binary cases in XLA mode must have either (a) each index appearing
     # exactly once in both the inputs (batch or contraction index), or
     # (b) appearing exactly once in an input and in the output (free index).
@@ -598,20 +585,17 @@ class EinsumGradTest(test.TestCase):
     self._check_gradient('sa,shb->shab', (2, 1), (2, 3, 4))
 
   def test_empty(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # From Transformer XL.
     self._check_gradient('ibnd,ijbn->jnd', (1, 0, 5, 10), (1, 1, 0, 5))
 
   @test_util.disable_xla('b/131919749')
   def test_reduced_indices(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     self._check_gradient('ba,b->', (3, 2), (3,))
     self._check_gradient('ab,ab->', (3, 4), (3, 4))
     self._check_gradient('abce,badf->abcd', (1, 2, 3, 4), (2, 1, 4, 3))
 
   @test_util.disable_xla('b/131919749')
   def test_repeated_indices(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     # Repeated indices.
     self._check_gradient('aba,a->b', (3, 4, 3), (3,))
     self._check_gradient('ijj,k->ik', (2, 3, 3), (4,))
@@ -622,14 +606,12 @@ class EinsumGradTest(test.TestCase):
 
   @test_util.disable_xla('b/131919749')
   def test_empty_with_repeated_indices(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     self._check_gradient('aab,bc->ac', (0, 0, 10), (10, 10))
     self._check_gradient('aab,bc->ac', (1, 1, 0), (0, 10))
     self._check_gradient('aaab,bc->c', (0, 0, 0, 3), (3, 4))
 
   @test_util.disable_xla('b/131919749')
   def test_broadcasting(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     self._check_gradient('...ij,...jk->...ik', (3, 2), (2, 4))
     self._check_gradient('ij...,jk...->ik...', (3, 2, 1), (2, 4))
     self._check_gradient('...ij,...jk->...ik', (3, 1, 3, 2), (1, 5, 2, 4))
@@ -641,7 +623,6 @@ class EinsumGradTest(test.TestCase):
     self._check_gradient('...i,...j,...k->...ijk', (1,), (1,), (1,))
 
   def test_long_cases(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     cases = [
         'abhe,hidj,jgba,hiab,gab->ed',
         # Tests from dask.
@@ -658,7 +639,6 @@ class EinsumGradTest(test.TestCase):
 
   @test_util.disable_xla('b/131919749')
   def test_long_cases_with_repeated_labels(self):
-    with compat.forward_compatibility_horizon(2019, 10, 19):
     cases = [
         # Tests from dask.
         'fdf,cdd,ccd,afe->ae',