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[TF:XLA] Enable XLA through autojit for all tensorflow/python/kernel_test/ tests.

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Some test methods are disabled, but all tests now have a new "_xla" version of the test for XLA:GPU testing. This will run 2 different tests. One with XLA and one without.

PiperOrigin-RevId: 229149574
This commit is contained in:
A. Unique TensorFlower 2019-01-14 02:36:35 -08:00 committed by TensorFlower Gardener
parent 6dd6ad9fd7
commit 4ac9bda9d0
40 changed files with 422 additions and 55 deletions
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8
tensorflow/python/BUILD
View File

@ -1103,6 +1103,14 @@ py_library(
],
)
# Including this as a dependency will result in tests using
# :framework_test_lib to use XLA.
py_library(
name = "is_xla_test_true",
srcs = ["framework/is_xla_test_true.py"],
srcs_version = "PY2AND3",
)
py_library(
name = "distributed_framework_test_lib",
srcs_version = "PY2AND3",

1
tensorflow/python/framework/function_test.py
View File

@ -284,6 +284,7 @@ class FunctionTest(test.TestCase):
out, = sess.run(dlogits, {logits: x, labels: y})
self.assertAllClose(out, np.exp(prob - y))
@test_util.disable_xla("This test never passed for XLA")
def testCustomGradientError(self):
dtype = dtypes.float32

29
tensorflow/python/framework/is_xla_test_true.py Normal file
View File

@ -0,0 +1,29 @@
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Including this as a dependency will result in Tensorflow tests using XLA.
This function is defined by default in test_util.py to False. The test_util then
attempts to import this module. If this file is made available through the BUILD
rule, then this function is overridden and will instead cause Tensorflow graphs
to be compiled with XLA.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
def is_xla_enabled():
"""Returns true to state XLA should be enabled for Tensorflow tests."""
return True

166
tensorflow/python/framework/test_util.py
View File

@ -82,6 +82,19 @@ from tensorflow.python.util.protobuf import compare
from tensorflow.python.util.tf_export import tf_export
# If the above import is made available through the BUILD rule, then this
# function is overridden and will instead return True and cause Tensorflow
# graphs to be compiled with XLA.
def is_xla_enabled():
return False
try:
from tensorflow.python.framework.is_xla_test_true import is_xla_enabled # pylint: disable=g-import-not-at-top
except:
pass
@tf_export("test.gpu_device_name")
def gpu_device_name():
"""Returns the name of a GPU device if available or the empty string."""
@ -97,6 +110,7 @@ def assert_ops_in_graph(expected_ops, graph):
Args:
expected_ops: `dict<string, string>` of op name to op type.
graph: Graph to check.
Returns:
`dict<string, node>` of node name to node.
@ -149,7 +163,7 @@ def assert_equal_graph_def_v1(actual, expected, checkpoint_v2=False):
actual: The `GraphDef` we have.
expected: The `GraphDef` we expected.
checkpoint_v2: boolean determining whether to ignore randomized attribute
values that appear in V2 checkpoints.
values that appear in V2 checkpoints.
Raises:
AssertionError: If the `GraphDef`s do not match.
@ -360,7 +374,8 @@ def skip_if(condition):
Args:
condition: Either an expression that can be used in "if not condition"
statement, or a callable whose result should be a boolean.
statement, or a callable whose result should be a boolean.
Returns:
The wrapped function
"""
@ -483,9 +498,11 @@ def disable_control_flow_v2(unused_msg):
Returns:
The wrapped function with _disable_control_flow_v2 attr set to True.
"""
def wrapper(func):
func._disable_control_flow_v2 = True
return func
return wrapper
@ -568,6 +585,7 @@ def assert_no_new_tensors(f):
Args:
f: The test case to run.
Returns:
The decorated test case.
"""
@ -727,6 +745,7 @@ def assert_no_garbage_created(f):
Args:
f: The function to decorate.
Returns:
The decorated function.
"""
@ -799,8 +818,8 @@ def _combine_named_parameters(**kwargs):
can be computed using `times()`.
Args:
**kwargs: keyword arguments of form `option=[possibilities, ...]`
or `option=the_only_possibility`.
**kwargs: keyword arguments of form `option=[possibilities, ...]` or
`option=the_only_possibility`.
Returns:
a list of dictionaries for each combination. Keys in the dictionaries are
@ -838,8 +857,8 @@ def generate_combinations_with_testcase_name(**kwargs):
parameterized tests.
Args:
**kwargs: keyword arguments of form `option=[possibilities, ...]`
or `option=the_only_possibility`.
**kwargs: keyword arguments of form `option=[possibilities, ...]` or
`option=the_only_possibility`.
Returns:
a list of dictionaries for each combination. Keys in the dictionaries are
@ -866,11 +885,12 @@ def generate_combinations_with_testcase_name(**kwargs):
def run_all_in_graph_and_eager_modes(cls):
"""Execute all test methods in the given class with and without eager."""
base_decorator = run_in_graph_and_eager_modes
for name, value in cls.__dict__.copy().items():
if (callable(value) and
name.startswith(unittest.TestLoader.testMethodPrefix) and
not (name.startswith("testSkipEager")
or name.startswith("test_skip_eager"))):
for name in dir(cls):
value = getattr(cls, name)
if callable(value) and name.startswith(
unittest.TestLoader.testMethodPrefix) and not (
name.startswith("testSkipEager") or
name.startswith("test_skip_eager") or name == "test_session"):
setattr(cls, name, base_decorator(value))
return cls
@ -917,8 +937,8 @@ def run_in_graph_and_eager_modes(func=None,
func: function to be annotated. If `func` is None, this method returns a
decorator the can be applied to a function. If `func` is not None this
returns the decorator applied to `func`.
config: An optional config_pb2.ConfigProto to use to configure the
session when executing graphs.
config: An optional config_pb2.ConfigProto to use to configure the session
when executing graphs.
use_gpu: If True, attempt to run as many operations as possible on GPU.
reset_test: If True, tearDown and SetUp the test case between the two
executions of the test (once with and once without eager execution).
@ -932,6 +952,7 @@ def run_in_graph_and_eager_modes(func=None,
collected elsewhere in the unit test file will not work). Additionally,
checks that nothing still has a reference to Tensors that the test
allocated.
Returns:
Returns a decorator that will run the decorated test method twice:
once by constructing and executing a graph in a session and once with
@ -992,9 +1013,10 @@ def py_func_if_in_function(f):
if not ops.get_default_graph()._building_function:
return f(*args, **kwds)
tensor_args, tensor_indices = zip(
*[(x, i) for i, x in enumerate(args)
if isinstance(x, (ops.Tensor, variables.Variable))])
tensor_args, tensor_indices = zip(*[(x, i)
for i, x in enumerate(args)
if isinstance(x, (ops.Tensor,
variables.Variable))])
def inner_f(*inner_tensor_args):
my_args = list(args)
@ -1056,6 +1078,7 @@ def deprecated_graph_mode_only(func=None):
func: function to be annotated. If `func` is None, this method returns a
decorator the can be applied to a function. If `func` is not None this
returns the decorator applied to `func`.
Returns:
Returns a decorator that will run the decorated test method in graph mode.
"""
@ -1390,8 +1413,7 @@ class FakeEagerSession(object):
class ErrorLoggingSession(session.Session):
"""Wrapper around a Session that logs errors in run().
"""
"""Wrapper around a Session that logs errors in run()."""
def run(self, *args, **kwargs):
try:
@ -1405,13 +1427,56 @@ class ErrorLoggingSession(session.Session):
raise
# The description is just for documentation purposes.
def disable_xla(description):
def disable_xla_impl(func):
"""Execute the test method only if xla is not enabled."""
def decorator(func):
def decorated(self, *args, **kwargs):
if is_xla_enabled():
return
else:
return func(self, *args, **kwargs)
return decorated
if func is not None:
return decorator(func)
return decorator
return disable_xla_impl
# The description is just for documentation purposes.
def disable_all_xla(description):
def disable_all_impl(cls):
"""Execute all test methods in this class only if xla is not enabled."""
base_decorator = disable_xla
for name in dir(cls):
value = getattr(cls, name)
if callable(value) and name.startswith(
"test") and not name == "test_session":
setattr(cls, name, base_decorator(value))
return cls
return disable_all_impl
@tf_export("test.TestCase")
class TensorFlowTestCase(googletest.TestCase):
"""Base class for tests that need to test TensorFlow.
"""
"""Base class for tests that need to test TensorFlow."""
def __init__(self, methodName="runTest"): # pylint: disable=invalid-name
super(TensorFlowTestCase, self).__init__(methodName)
if is_xla_enabled():
os.putenv(
"TF_XLA_FLAGS", "--tf_xla_auto_jit=2 --tf_xla_min_cluster_size=1 "
"--tf_xla_enable_lazy_compilation=false")
self._threads = []
self._tempdir = None
self._cached_session = None
@ -1489,9 +1554,9 @@ class TensorFlowTestCase(googletest.TestCase):
```
Args:
stream: The stream whose writes should be captured. This
stream must have a file descriptor, support writing via using that
file descriptor, and must have a `.flush()` method.
stream: The stream whose writes should be captured. This stream must have
a file descriptor, support writing via using that file descriptor, and
must have a `.flush()` method.
Yields:
A `CapturedWrites` object that contains all writes to the specified stream
@ -1840,7 +1905,6 @@ class TensorFlowTestCase(googletest.TestCase):
self._threads.append(ret)
return ret
# pylint: enable=invalid-name
@py_func_if_in_function
def assertNear(self, f1, f2, err, msg=None):
@ -1857,9 +1921,8 @@ class TensorFlowTestCase(googletest.TestCase):
"""
# f1 == f2 is needed here as we might have: f1, f2 = inf, inf
self.assertTrue(
f1 == f2 or math.fabs(f1 - f2) <= err,
"%f != %f +/- %f%s" % (f1, f2, err, " (%s)" % msg
if msg is not None else ""))
f1 == f2 or math.fabs(f1 - f2) <= err, "%f != %f +/- %f%s" %
(f1, f2, err, " (%s)" % msg if msg is not None else ""))
@py_func_if_in_function
def assertArrayNear(self, farray1, farray2, err, msg=None):
@ -2028,11 +2091,11 @@ class TensorFlowTestCase(googletest.TestCase):
Args:
a: The expected numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor), or any arbitrarily nested of
structure of these.
numpy `ndarray` (including Tensor), or any arbitrarily nested of
structure of these.
b: The actual numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor), or any arbitrarily nested of
structure of these.
numpy `ndarray` (including Tensor), or any arbitrarily nested of
structure of these.
rtol: relative tolerance.
atol: absolute tolerance.
msg: Optional message to report on failure.
@ -2160,8 +2223,8 @@ class TensorFlowTestCase(googletest.TestCase):
"""Assert element values are all greater than a target value.
Args:
a: The numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor).
a: The numpy `ndarray`, or anything that can be converted into a numpy
`ndarray` (including Tensor).
comparison_target: The target value of comparison.
"""
a = self._GetNdArray(a)
@ -2172,8 +2235,8 @@ class TensorFlowTestCase(googletest.TestCase):
"""Assert element values are all less than a target value.
Args:
a: The numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor).
a: The numpy `ndarray`, or anything that can be converted into a numpy
`ndarray` (including Tensor).
comparison_target: The target value of comparison.
"""
a = self._GetNdArray(a)
@ -2184,8 +2247,8 @@ class TensorFlowTestCase(googletest.TestCase):
"""Assert element values are all greater than or equal to a target value.
Args:
a: The numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor).
a: The numpy `ndarray`, or anything that can be converted into a numpy
`ndarray` (including Tensor).
comparison_target: The target value of comparison.
"""
a = self._GetNdArray(a)
@ -2196,8 +2259,8 @@ class TensorFlowTestCase(googletest.TestCase):
"""Assert element values are all less than or equal to a target value.
Args:
a: The numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor).
a: The numpy `ndarray`, or anything that can be converted into a numpy
`ndarray` (including Tensor).
comparison_target: The target value of comparison.
"""
a = self._GetNdArray(a)
@ -2245,7 +2308,7 @@ class TensorFlowTestCase(googletest.TestCase):
Args:
target: The numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor).
numpy `ndarray` (including Tensor).
lower_bound: lower bound of the range
upper_bound: upper bound of the range
open_lower_bound: (`bool`) whether the lower bound is open (i.e., > rather
@ -2279,8 +2342,8 @@ class TensorFlowTestCase(googletest.TestCase):
str(upper_bound) + (")" if open_upper_bound else "]"))
violations = (
np.less_equal(target, lower_bound)
if open_lower_bound else np.less(target, lower_bound))
np.less_equal(target, lower_bound) if open_lower_bound else np.less(
target, lower_bound))
violations = np.logical_or(
violations,
np.greater_equal(target, upper_bound)
@ -2299,7 +2362,7 @@ class TensorFlowTestCase(googletest.TestCase):
Args:
target: The numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor).
numpy `ndarray` (including Tensor).
expected_set: (`list`, `tuple` or `set`) The closed set that the elements
of the value of `target` are expected to fall into.
@ -2321,7 +2384,7 @@ class TensorFlowTestCase(googletest.TestCase):
Args:
target: The numpy `ndarray`, or anything that can be converted into a
numpy `ndarray` (including Tensor).
numpy `ndarray` (including Tensor).
expected_dtype: Expected data type.
"""
target = self._GetNdArray(target)
@ -2342,9 +2405,9 @@ class TensorFlowTestCase(googletest.TestCase):
Args:
exception_type: The expected type of exception that should be raised.
expected_err_re_or_predicate: If this is callable, it should be a function
of one argument that inspects the passed-in exception and
returns True (success) or False (please fail the test). Otherwise, the
error message is expected to match this regular expression partially.
of one argument that inspects the passed-in exception and returns True
(success) or False (please fail the test). Otherwise, the error message
is expected to match this regular expression partially.
Returns:
A context manager to surround code that is expected to raise an
@ -2445,6 +2508,7 @@ class TensorFlowTestCase(googletest.TestCase):
def _create_session(self, graph, config, force_gpu):
"""See session() for details."""
def prepare_config(config):
"""Returns a config for sessions.
@ -2547,10 +2611,10 @@ def create_local_cluster(num_workers,
Args:
num_workers: Number of worker servers to start.
num_ps: Number of PS servers to start.
protocol: Communication protocol. Allowed values are documented in
the documentation of `tf.train.Server`.
worker_config: (optional) ConfigProto to initialize workers. Can be used
to instantiate multiple devices etc.
protocol: Communication protocol. Allowed values are documented in the
documentation of `tf.train.Server`.
worker_config: (optional) ConfigProto to initialize workers. Can be used to
instantiate multiple devices etc.
ps_config: (optional) ConfigProto to initialize PS servers.
Returns:

130
tensorflow/python/kernel_tests/BUILD
View File

@ -131,6 +131,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
],
grpc_enabled = True,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -145,6 +146,7 @@ cuda_py_test(
"//tensorflow/python:platform_benchmark",
],
tags = ["no_windows"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -161,6 +163,7 @@ cuda_py_test(
"//tensorflow/python:platform",
"//tensorflow/python:platform_benchmark",
],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -226,6 +229,7 @@ cuda_py_test(
],
shard_count = 5,
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -282,6 +286,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:gradients",
],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -387,6 +392,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:linalg_ops",
],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -645,6 +651,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
tags = ["optonly"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -659,6 +666,7 @@ cuda_py_test(
"//tensorflow/python:linalg_ops",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -671,6 +679,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:linalg_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -684,6 +693,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:linalg_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -695,6 +705,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:linalg_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -713,6 +724,7 @@ cuda_py_test(
"//tensorflow/python:platform",
"//tensorflow/python:random_ops",
],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -795,6 +807,7 @@ cuda_py_test(
"//tensorflow/python:resource_variable_ops",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -853,6 +866,7 @@ cuda_py_test(
"//tensorflow/python:resource_variable_ops",
],
tags = ["noasan"], # http://b/32635055
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -1159,6 +1173,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1174,6 +1189,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -1290,6 +1306,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1311,6 +1328,7 @@ cuda_py_test(
"noguitar",
"notap",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1326,6 +1344,7 @@ cuda_py_test(
"//tensorflow/python:variables",
],
tags = ["notsan"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1342,6 +1361,7 @@ cuda_py_test(
],
shard_count = 2,
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -1374,6 +1394,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1385,6 +1406,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1413,6 +1435,7 @@ cuda_py_test(
"noasan", # times out
"optonly", # times out
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1425,6 +1448,7 @@ cuda_py_test(
"//tensorflow/python:client",
"//tensorflow/python:client_testlib",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1441,6 +1465,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
shard_count = 10,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1455,6 +1480,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
shard_count = 20,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1468,6 +1494,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1482,6 +1509,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:platform",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1497,6 +1525,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1509,6 +1538,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1527,6 +1557,7 @@ cuda_py_test(
"//tensorflow/python:framework",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1542,6 +1573,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:util",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1560,6 +1592,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:util",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1600,6 +1633,7 @@ cuda_py_test(
],
shard_count = 16,
tags = ["no_gpu"], # TODO(b/117928656)
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -1640,6 +1674,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1654,6 +1689,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1668,6 +1704,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1679,6 +1716,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1692,6 +1730,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:platform",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1707,6 +1746,7 @@ cuda_py_test(
"//tensorflow/python:state_ops",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1721,6 +1761,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1733,6 +1774,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
],
tags = ["manual"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1748,6 +1790,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:gradients",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1762,6 +1805,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:gradients",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1774,6 +1818,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1786,6 +1831,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1812,6 +1858,7 @@ cuda_py_test(
grpc_enabled = True,
shard_count = 2,
tags = ["no_windows"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1827,6 +1874,7 @@ cuda_py_test(
"//tensorflow/python:gradients",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1841,6 +1889,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:gradients",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1854,6 +1903,7 @@ cuda_py_test(
"//tensorflow/python:gradients",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1881,6 +1931,7 @@ cuda_py_test(
"noasan",
"notap",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1898,6 +1949,7 @@ cuda_py_test(
"//tensorflow/python/ops/linalg",
],
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1913,6 +1965,7 @@ cuda_py_test(
"//tensorflow/python:nn",
"//tensorflow/python:nn_grad",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1929,6 +1982,7 @@ cuda_py_test(
"//tensorflow/python:platform",
"//tensorflow/python/ops/linalg",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1942,6 +1996,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
],
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1959,6 +2014,7 @@ cuda_py_test(
"//tensorflow/python:variables",
],
shard_count = 20,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1972,6 +2028,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -1987,6 +2044,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:numerics",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2000,6 +2058,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
],
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2014,6 +2073,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2026,6 +2086,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2040,6 +2101,7 @@ cuda_py_test(
"//tensorflow/python:errors",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2058,6 +2120,7 @@ cuda_py_test(
"//tensorflow/python/eager:function",
],
tags = ["no_windows"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2071,6 +2134,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:string_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2086,6 +2150,7 @@ cuda_py_test(
],
shard_count = 4,
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2106,6 +2171,7 @@ cuda_py_test(
"noguitar",
"notap",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2124,6 +2190,7 @@ cuda_py_test(
"//tensorflow/python/eager:backprop",
"//tensorflow/python:tf2",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2136,6 +2203,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2148,6 +2216,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2160,6 +2229,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2178,6 +2248,7 @@ cuda_py_test(
"//tensorflow/python:random_ops",
"//tensorflow/python:sparse_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2191,6 +2262,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2203,6 +2275,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:session_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2219,6 +2292,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:gradients",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2233,6 +2307,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2246,6 +2321,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2259,6 +2335,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2274,6 +2351,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2288,6 +2366,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -2332,6 +2411,7 @@ cuda_py_test(
"//tensorflow/python:sparse_grad",
"//tensorflow/python:sparse_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2356,6 +2436,7 @@ cuda_py_test(
"//tensorflow/python:random_ops",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2370,6 +2451,7 @@ cuda_py_test(
"//tensorflow/python:gradients",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2385,6 +2467,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2397,6 +2480,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:string_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2409,6 +2493,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:parsing_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2422,6 +2507,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:summary",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2437,6 +2523,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:summary",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2467,6 +2554,7 @@ cuda_py_test(
"//tensorflow/python/eager:context",
],
flaky = 1, # create_local_cluster sometimes times out.
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2479,6 +2567,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
tags = ["no_windows_gpu"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2497,6 +2586,7 @@ cuda_py_test(
"no_oss",
"optonly", # times out
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2509,6 +2599,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2526,6 +2617,7 @@ cuda_py_test(
"//tensorflow/python:state_ops_gen",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2542,6 +2634,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops",
"//tensorflow/python:nn_ops_gen",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2553,6 +2646,7 @@ cuda_py_test(
"//tensorflow/python:errors",
"//tensorflow/python:framework_for_generated_wrappers",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2572,6 +2666,7 @@ cuda_py_test(
tags = [
"no_gpu", # Flaky: b/80127739
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2587,6 +2682,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops",
],
tags = ["manual"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2600,6 +2696,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2618,6 +2715,7 @@ cuda_py_test(
tags = [
"optonly", # flaky timeouts unless optimized
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2631,6 +2729,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2659,6 +2758,7 @@ cuda_py_test(
"no_oss",
"optonly", # times out
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2676,6 +2776,7 @@ cuda_py_test(
],
# TODO(b/118842098): Re-enable this test in Kokoro.
tags = ["no_oss"],
xla_enable_strict_auto_jit = True,
)
tf_py_test(
@ -2704,6 +2805,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
],
tags = ["manual"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2717,6 +2819,7 @@ cuda_py_test(
"//tensorflow/python:nn_grad",
"//tensorflow/python:nn_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2735,6 +2838,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops_gen",
],
shard_count = 4,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2764,6 +2868,7 @@ cuda_py_test(
"//tensorflow/python/eager:context",
],
shard_count = 10,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2779,6 +2884,7 @@ cuda_py_test(
],
shard_count = 2,
tags = ["optonly"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2793,6 +2899,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:gradients",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2809,6 +2916,7 @@ cuda_py_test(
tags = [
"no_oss", # Requires 4GB+ RAM
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2822,6 +2930,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
tags = ["no_windows"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2845,6 +2954,7 @@ cuda_py_test(
"noasan",
"optonly", # b/77589990
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2864,6 +2974,7 @@ cuda_py_test(
"//tensorflow/python:platform",
"//tensorflow/python:sparse_ops",
],
xla_enable_strict_auto_jit = True,
)
# TODO(gpapan): Revisit the gradient of extract_image_patches_op to resolve
@ -2880,6 +2991,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
],
tags = ["notap"], # http://b/31080670
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2894,6 +3006,7 @@ cuda_py_test(
"//tensorflow/python:util",
"//tensorflow/python:data_flow_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2908,6 +3021,7 @@ cuda_py_test(
"//tensorflow/python:util",
"//tensorflow/python:data_flow_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2925,6 +3039,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2940,6 +3055,7 @@ cuda_py_test(
"nomsan",
"notsan",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2953,6 +3069,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops",
],
shard_count = 30,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2973,6 +3090,7 @@ cuda_py_test(
"//tensorflow/python:variables",
],
shard_count = 50,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -2993,6 +3111,7 @@ cuda_py_test(
"//tensorflow/python:variables",
],
shard_count = 50,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3013,6 +3132,7 @@ cuda_py_test(
"//tensorflow/python:variables",
],
shard_count = 50,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3038,6 +3158,7 @@ cuda_py_test(
"//tensorflow/python:variables",
],
shard_count = 20,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3055,6 +3176,7 @@ cuda_py_test(
"//tensorflow/python/ops/linalg",
],
shard_count = 20,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3068,6 +3190,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
],
shard_count = 20,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3085,6 +3208,7 @@ cuda_py_test(
data = ["//tensorflow/python/kernel_tests/testdata:self_adjoint_eig_op_test_files"],
shard_count = 20,
tags = ["no_windows"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3100,6 +3224,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
shard_count = 20,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3119,6 +3244,7 @@ cuda_py_test(
"no_oss", # b/117185141.
"nomsan", # TODO(b/117236102): Re-enable in msan build.
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3138,6 +3264,7 @@ cuda_py_test(
"no_windows_gpu",
"nomsan",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3153,6 +3280,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
],
shard_count = 20,
xla_enable_strict_auto_jit = True,
)
sycl_py_test(
@ -3399,6 +3527,7 @@ cuda_py_test(
"//tensorflow/python:while_v2",
],
grpc_enabled = True,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -3424,4 +3553,5 @@ cuda_py_test(
"//tensorflow/python:while_v2",
],
grpc_enabled = True,
xla_enable_strict_auto_jit = True,
)

1
tensorflow/python/kernel_tests/atrous_conv2d_test.py
View File

@ -139,6 +139,7 @@ class AtrousConv2DTest(test.TestCase):
y1.eval(), self.evaluate(y2), rtol=1e-2, atol=1e-2)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA") # larger error range
def testGradient(self):
with self.session(use_gpu=True):
# Input: [batch, height, width, input_depth]

2
tensorflow/python/kernel_tests/benchmark_test.py
View File

@ -26,6 +26,7 @@ import numpy as np
from tensorflow.core.util import test_log_pb2
from tensorflow.python.client import session
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import benchmark
from tensorflow.python.platform import gfile
@ -125,6 +126,7 @@ class BenchmarkTest(test.TestCase):
self.assertFalse(_ran_somebenchmark_2[0])
self.assertFalse(_ran_somebenchmark_but_shouldnt[0])
@test_util.disable_xla("This test never passed for XLA")
def testReportingBenchmark(self):
tempdir = test.get_temp_dir()
try:

4
tensorflow/python/kernel_tests/check_ops_test.py
View File

@ -889,6 +889,8 @@ class EnsureShapeTest(test.TestCase):
# Dynamic shape check
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA"
) # Dynamic shapes not supported now with XLA
def testEnsuresDynamicShape_RaisesError(self):
placeholder = array_ops.placeholder(dtypes.int32)
derived = math_ops.divide(placeholder, 3, name="MyDivide")
@ -902,6 +904,8 @@ class EnsureShapeTest(test.TestCase):
sess.run(derived, feed_dict={placeholder: feed_val})
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA"
) # Dynamic shapes not supported now with XLA
def testEnsuresDynamicShape_RaisesErrorDimUnknown(self):
placeholder = array_ops.placeholder(dtypes.int32)
derived = placeholder / 3

1
tensorflow/python/kernel_tests/cholesky_op_test.py
View File

@ -163,6 +163,7 @@ class CholeskyOpTest(test.TestCase):
with self.assertRaises(ValueError):
linalg_ops.cholesky(tensor3)
@test_util.disable_xla("This test never passed for XLA") # all nan on XLA
def testNotInvertibleCPU(self):
# The input should be invertible.
with self.session(use_gpu=True):

5
tensorflow/python/kernel_tests/concat_op_test.py
View File

@ -33,6 +33,7 @@ from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@test_util.disable_all_xla("This test never passed for XLA")
class ConcatOpTest(test.TestCase):
@test_util.run_deprecated_v1
@ -640,6 +641,8 @@ class ConcatOpTest(test.TestCase):
output = self.evaluate(c)
self.assertAllEqual([[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]], output)
@test_util.disable_all_xla("This test never passed for XLA")
class ConcatOffsetTest(test.TestCase):
def testBasic(self):
@ -683,6 +686,8 @@ class ConcatOffsetTest(test.TestCase):
self.evaluate(off)
@test_util.run_deprecated_v1
@test_util.disable_xla(
"This test never passed for XLA") # Different error message on XLA
def testSizeMismatch(self):
cdim = constant_op.constant(1, dtypes.int32)
s0 = constant_op.constant([2, 3, 5], dtypes.int32)

2
tensorflow/python/kernel_tests/control_flow_ops_py_test.py
View File

@ -2380,6 +2380,8 @@ class ControlFlowTest(test.TestCase):
self.assertEqual(i_val, 3)
self.assertAllClose(x_val, 1.0)
@test_util.disable_xla("This test never passed for XLA"
) # Resource variable issue for ControlFlowV2
@test_util.run_gpu_only
def testGpuResourceAccess(self):
with ops.device(test.gpu_device_name()):

1
tensorflow/python/kernel_tests/depthtospace_op_test.py
View File

@ -295,6 +295,7 @@ class DepthToSpaceTest(test.TestCase):
actual_vals, expected_vals = self.evaluate([actual, expected])
self.assertTrue(np.array_equal(actual_vals, expected_vals))
@test_util.disable_xla("This test never passed for XLA")
def testAgainstTranspose(self):
self.compareToTranspose(3, 2, 3, 1, 2, "NHWC", False)
self.compareToTranspose(3, 2, 3, 2, 2, "NHWC", False)

2
tensorflow/python/kernel_tests/depthwise_conv_op_test.py
View File

@ -481,6 +481,7 @@ class DepthwiseConv2DTest(test.TestCase):
data_format="NCHW")
@test_util.run_v1_only("b/120545219")
@test_util.disable_xla("This test never passed for XLA")
def testDepthwiseConv2DFilterGrad(self):
for index, (input_size, filter_size, output_size, stride,
padding) in enumerate(CheckGradConfigsToTest()):
@ -612,6 +613,7 @@ class DepthwiseConv2DTest(test.TestCase):
cpu_value = _GetVal(use_gpu=False)
self.assertAllClose(cpu_value, gpu_value, rtol=1e-4, atol=1e-4)
@test_util.disable_xla("This test never passed for XLA")
def testDepthwiseConv2DFilterGradCompare(self):
for index, (input_size, filter_size, output_size, stride,
padding) in enumerate(ConfigsToTest()):

2
tensorflow/python/kernel_tests/diag_op_test.py
View File

@ -65,6 +65,7 @@ class MatrixDiagTest(test.TestCase):
array_ops.matrix_diag(0)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testInvalidShapeAtEval(self):
with self.session(use_gpu=True):
v = array_ops.placeholder(dtype=dtypes_lib.float32)
@ -269,6 +270,7 @@ class MatrixDiagPartTest(test.TestCase):
array_ops.matrix_diag_part(0)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testInvalidShapeAtEval(self):
with self.session(use_gpu=True):
v = array_ops.placeholder(dtype=dtypes_lib.float32)

17
tensorflow/python/kernel_tests/distributions/BUILD
View File

@ -23,6 +23,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -42,6 +43,7 @@ cuda_py_test(
"//tensorflow/python:platform_test",
],
shard_count = 3,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -54,6 +56,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -71,6 +74,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -86,6 +90,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -105,6 +110,7 @@ cuda_py_test(
"//tensorflow/python:platform_test",
"//tensorflow/python:random_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -119,6 +125,7 @@ cuda_py_test(
"//tensorflow/python:framework_test_lib",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -139,6 +146,7 @@ cuda_py_test(
"noguitar", # b/110489471
"notap", # b/110489471
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -154,6 +162,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -169,6 +178,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -184,6 +194,7 @@ cuda_py_test(
"//tensorflow/python:nn_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -200,6 +211,7 @@ cuda_py_test(
"//tensorflow/python:platform_test",
],
tags = ["manual"], # b/69001419
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -224,6 +236,7 @@ cuda_py_test(
# disable to avoid false positives from scipy.
"nomsan",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -240,6 +253,7 @@ cuda_py_test(
"//tensorflow/python:framework_test_lib",
"//tensorflow/python:math_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -258,6 +272,7 @@ cuda_py_test(
"//tensorflow/python:platform_test",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -274,6 +289,7 @@ cuda_py_test(
"//tensorflow/python:platform_test",
"//tensorflow/python:variables",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -291,4 +307,5 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)

4
tensorflow/python/kernel_tests/functional_ops_test.py
View File

@ -58,6 +58,7 @@ def simple_scoped_fn(a, x):
@test_util.with_control_flow_v2
@test_util.disable_all_xla("This test never passed for XLA")
class FunctionalOpsTest(test.TestCase):
@test_util.run_in_graph_and_eager_modes
@ -826,6 +827,8 @@ class FunctionalOpsTest(test.TestCase):
self.assertAllEqual(Run(100., True), 5050.)
@test_util.run_v1_only("b/120545219")
@test_util.disable_xla(
"This test never passed for XLA") # Different error message
def testWhileError(self):
for use_gpu in (True, False):
with ops.Graph().as_default() as g:
@ -1102,6 +1105,7 @@ class FunctionalOpsTest(test.TestCase):
# TODO(akshayka): Replace `function.Defun` with tf.contrib.eager.defun` in the
# below test cases.
@test_util.disable_all_xla("This test never passed for XLA")
class PartitionedCallTest(test.TestCase):
@test_util.run_deprecated_v1

3
tensorflow/python/kernel_tests/gather_nd_op_test.py
View File

@ -34,6 +34,7 @@ from tensorflow.python.ops import variables
from tensorflow.python.platform import test
@test_util.disable_all_xla("This test never passed for XLA")
class GatherNdTest(test.TestCase):
def _testSimpleDtype(self, dtype):
@ -56,6 +57,7 @@ class GatherNdTest(test.TestCase):
self._testSimpleDtype("|S") # byte strings in python2 + 3
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testEmptyIndicesAndParamsOKButJustEmptyParamsFails(self):
with self.session(use_gpu=True):
params = np.ones((3, 3), dtype=np.float32)
@ -358,6 +360,7 @@ class GatherNdTest(test.TestCase):
self.assertAllEqual(expected_grads, ops.convert_to_tensor(grads).eval())
@test_util.disable_all_xla("This test never passed for XLA")
class GatherNdOpBenchmark(test.Benchmark):
def benchmark_gather_nd_op(self):

2
tensorflow/python/kernel_tests/gather_op_test.py
View File

@ -213,6 +213,8 @@ class GatherTest(test.TestCase, parameterized.TestCase):
array_ops.gather(params, [[7]], axis=1).eval()
@test_util.run_deprecated_v1
@test_util.disable_xla(
"This test never passed for XLA") # Different error message.
def testBadAxis(self):
with self.session(use_gpu=True):
params = [0, 1, 2]

16
tensorflow/python/kernel_tests/linalg/BUILD
View File

@ -22,6 +22,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -38,6 +39,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -60,6 +62,7 @@ cuda_py_test(
"noasan", # times out, b/63678675
"optonly", # times out
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -76,6 +79,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -98,6 +102,7 @@ cuda_py_test(
"noasan",
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -120,6 +125,7 @@ cuda_py_test(
"noasan", # times out, b/63678675
"optonly", # times out
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -144,6 +150,7 @@ cuda_py_test(
"noasan", # times out, b/63678675
"optonly", # times out, b/79171797
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -166,6 +173,7 @@ cuda_py_test(
"noasan",
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -187,6 +195,7 @@ cuda_py_test(
"noasan",
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -209,6 +218,7 @@ cuda_py_test(
"noasan", # times out, b/63678675
"optonly", # times out
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -229,6 +239,7 @@ cuda_py_test(
"noasan",
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -251,6 +262,7 @@ cuda_py_test(
"noasan",
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -270,6 +282,7 @@ cuda_py_test(
"noasan",
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -290,6 +303,7 @@ cuda_py_test(
"noasan", # times out
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -310,6 +324,7 @@ cuda_py_test(
"noasan",
"optonly",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -328,4 +343,5 @@ cuda_py_test(
],
shard_count = 5,
tags = ["optonly"], # Test is flaky without optimization.
xla_enable_strict_auto_jit = True,
)

1
tensorflow/python/kernel_tests/pool_test.py
View File

@ -303,6 +303,7 @@ class PoolingTest(test.TestCase):
self.assertLess(err, err_tolerance)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA") # Much larger error
def testGradient1D(self):
with self.session(use_gpu=test.is_gpu_available()):
for padding in ["SAME", "VALID"]:

20
tensorflow/python/kernel_tests/pooling_ops_test.py
View File

@ -730,6 +730,7 @@ class PoolingTest(test.TestCase):
t = nn_ops.max_pool(
t, ksize=ksize, strides=strides, padding="SAME").eval()
@test_util.disable_xla("This test never passed for XLA")
def testDepthwiseMaxPoolInvalidConfigs(self):
self._testDepthwiseMaxPoolInvalidConfig(
[1, 2, 2, 4], [1, 2, 2, 2], [1, 1, 1, 2],
@ -1174,6 +1175,7 @@ class PoolingTest(test.TestCase):
use_gpu=use_gpu)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testMaxPoolGrad(self):
for (data_format, use_gpu) in GetTestConfigs():
self._testMaxPoolGradValidPadding1_1(data_format, use_gpu)
@ -1210,6 +1212,7 @@ class PoolingTest(test.TestCase):
[1, window_rows, window_cols, 1],
[1, row_stride, col_stride, 1], padding)
@test_util.disable_xla("This test never passed for XLA")
def _testMaxPoolGradDirect(self, input_data, output_backprop,
expected_input_backprop, input_sizes, output_sizes,
window_rows, window_cols, row_stride, col_stride,
@ -1625,6 +1628,7 @@ class PoolingTest(test.TestCase):
use_gpu=use_gpu)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testMaxPoolGradGrad(self):
for (data_format, use_gpu) in GetTestConfigs():
self._testMaxPoolGradGradValidPadding1_1(data_format, use_gpu)
@ -1659,6 +1663,7 @@ class PoolingTest(test.TestCase):
[1, row_stride, col_stride, 1], padding)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testAvgPoolGrad(self):
for (data_format, use_gpu) in GetTestConfigs():
self._testAvgPoolGradValidPadding1_1(data_format, use_gpu)
@ -1818,6 +1823,7 @@ class PoolingTest(test.TestCase):
padding="SAME")
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testOpEdgeCases(self):
with self.session(use_gpu=test.is_gpu_available()) as sess:
pool_funcs = [nn_ops.max_pool, nn_ops.avg_pool]
@ -1893,9 +1899,17 @@ if __name__ == "__main__":
padding_) in GetShrunkInceptionMaxPoolShapes():
setattr(PoolingTest, "testMaxPoolFwd_" + name_,
GetMaxPoolFwdTest(input_size_, filter_size_, stride_, padding_))
setattr(PoolingTest, "testMaxPoolGrad_" + name_,
GetMaxPoolGradTest(input_size_, filter_size_, output_size_, stride_,
padding_))
if name_ == "maxpool5":
setattr(
PoolingTest, "testMaxPoolGrad_" + name_,
test_util.disable_xla("maxpool5 fails while all others pass")(
GetMaxPoolGradTest(input_size_, filter_size_, output_size_,
stride_, padding_)))
else:
setattr(
PoolingTest, "testMaxPoolGrad_" + name_,
GetMaxPoolGradTest(input_size_, filter_size_, output_size_, stride_,
padding_))
setattr(PoolingTest, "testMaxPoolGradGrad_" + name_,
GetMaxPoolGradGradTest(input_size_, filter_size_, output_size_,
stride_, padding_))

8
tensorflow/python/kernel_tests/random/BUILD
View File

@ -45,6 +45,7 @@ cuda_py_test(
"//tensorflow/python:math_ops",
"//tensorflow/python:random_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -64,6 +65,7 @@ cuda_py_test(
"//tensorflow/python:random_ops",
],
shard_count = 3,
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -75,6 +77,7 @@ cuda_py_test(
"//tensorflow/python:client_testlib",
"//tensorflow/python:random_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -88,6 +91,7 @@ cuda_py_test(
"//tensorflow/python:framework_for_generated_wrappers",
"//tensorflow/python:random_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -103,6 +107,7 @@ cuda_py_test(
"//tensorflow/python:random_ops",
"//tensorflow/python:stateless_random_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -120,6 +125,7 @@ cuda_py_test(
],
shard_count = 4,
tags = ["nozapfhahn"],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -137,6 +143,7 @@ cuda_py_test(
"//tensorflow/python:random_grad",
"//tensorflow/python:random_ops",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -152,4 +159,5 @@ cuda_py_test(
"//tensorflow/python:platform",
"//tensorflow/python:random_ops",
],
xla_enable_strict_auto_jit = True,
)

1
tensorflow/python/kernel_tests/random/random_ops_test.py
View File

@ -257,6 +257,7 @@ class TruncatedNormalTest(test.TestCase):
self.assertAllEqual(rnd1, rnd2)
@test_util.disable_all_xla("This never passed on XLA")
class RandomUniformTest(RandomOpTestCommon):
def _Sampler(self, num, minv, maxv, dtype, use_gpu, seed=None):

1
tensorflow/python/kernel_tests/relu_op_test.py
View File

@ -86,6 +86,7 @@ class ReluTest(test.TestCase):
self.assertAllClose(np_relu, tf_relu)
self.assertShapeEqual(np_relu, tf_relu)
@test_util.disable_xla("This test never passed for XLA")
def testReluInt8x4BadShape(self):
if not test.is_gpu_available(cuda_only=True):
self.skipTest("No GPU available")

1
tensorflow/python/kernel_tests/resource_variable_ops_test.py
View File

@ -741,6 +741,7 @@ class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
@test_util.run_in_graph_and_eager_modes
@test_util.run_v1_only("b/120545219")
@test_util.disable_xla("This test never passed for XLA")
def testDestroyResource(self):
v = resource_variable_ops.ResourceVariable(3.0, name="var0")
self.evaluate(variables.global_variables_initializer())

2
tensorflow/python/kernel_tests/scan_ops_test.py
View File

@ -70,6 +70,7 @@ def handle_options(func, x, axis, exclusive, reverse):
return x
@test_util.disable_all_xla("This test never passed for XLA")
class CumsumTest(test.TestCase):
valid_dtypes = [
@ -193,6 +194,7 @@ class CumsumTest(test.TestCase):
self._compareGradient([5, 10], axis, exclusive, reverse)
@test_util.disable_all_xla("This test never passed for XLA")
class CumprodTest(test.TestCase):
valid_dtypes = [

1
tensorflow/python/kernel_tests/scatter_nd_ops_test.py
View File

@ -295,6 +295,7 @@ class StatefulScatterNdTest(test.TestCase):
updates).get_shape().as_list(), shape)
@test_util.run_v1_only("b/120545219")
@test_util.disable_xla("This test never passed for XLA")
def testResVarInvalidOutputShape(self):
res = variables.Variable(
initial_value=lambda: array_ops.zeros(shape=[], dtype=dtypes.float32),

8
tensorflow/python/kernel_tests/signal/BUILD
View File

@ -29,6 +29,7 @@ cuda_py_tests(
"//tensorflow/python:spectral_ops_test_util",
"//tensorflow/python/ops/signal",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_tests(
@ -45,6 +46,7 @@ cuda_py_tests(
],
shard_count = 4,
tags = ["optonly"],
xla_enable_strict_auto_jit = True,
)
cuda_py_tests(
@ -56,6 +58,7 @@ cuda_py_tests(
"//tensorflow/python:client_testlib",
"//tensorflow/python/ops/signal",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_tests(
@ -70,6 +73,7 @@ cuda_py_tests(
"//tensorflow/python/ops/signal",
"//tensorflow/python:spectral_ops_test_util",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_tests(
@ -87,6 +91,7 @@ cuda_py_tests(
"//tensorflow/python/ops/signal",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_tests(
@ -104,6 +109,7 @@ cuda_py_tests(
"//tensorflow/python/ops/signal",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_tests(
@ -125,6 +131,7 @@ cuda_py_tests(
"//tensorflow/python/ops/signal",
],
tags = ["nomac"],
xla_enable_strict_auto_jit = True,
)
cuda_py_tests(
@ -140,4 +147,5 @@ cuda_py_tests(
"//tensorflow/python/ops/signal",
"//tensorflow/python:platform_test",
],
xla_enable_strict_auto_jit = True,
)

1
tensorflow/python/kernel_tests/signal/fft_ops_test.py
View File

@ -465,6 +465,7 @@ class RFFTOpsTest(BaseFFTOpsTest):
gen_complex(complex_dims), rank, (size,) * rank)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testError(self):
with spectral_ops_test_util.fft_kernel_label_map():
for rank in VALID_FFT_RANKS:

1
tensorflow/python/kernel_tests/spacetodepth_op_test.py
View File

@ -285,6 +285,7 @@ class SpaceToDepthTest(test.TestCase):
actual_vals, expected_vals = self.evaluate([actual, expected])
self.assertTrue(np.array_equal(actual_vals, expected_vals))
@test_util.disable_xla("This test never passed for XLA")
def testAgainstTranspose(self):
self.compareToTranspose(3, 2, 3, 1, 2, "NHWC", False)
self.compareToTranspose(1, 2, 3, 2, 2, "NHWC", False)

1
tensorflow/python/kernel_tests/split_op_test.py
View File

@ -373,6 +373,7 @@ class SplitOpTest(test.TestCase):
assert s1.shape.as_list() == [1]
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testNonexistentDimTensor(self):
x = array_ops.placeholder(dtypes.int32)
values = np.zeros([5, 30])

3
tensorflow/python/ops/bitwise_ops_test.py
View File

@ -35,6 +35,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
super(BitwiseOpTest, self).__init__(method_name)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testBinaryOps(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16, dtypes.uint32, dtypes.uint64]
@ -72,6 +73,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
self.assertAllEqual(truth, popcnt_result)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testInvertOp(self):
dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
dtypes.uint8, dtypes.uint16, dtypes.uint32, dtypes.uint64]
@ -97,6 +99,7 @@ class BitwiseOpTest(test_util.TensorFlowTestCase):
self.assertAllEqual(inverted, expected)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testShiftsWithPositiveLHS(self):
dtype_list = [np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64]

1
tensorflow/python/ops/nn_batchnorm_test.py
View File

@ -206,6 +206,7 @@ class BatchNormalizationTest(test.TestCase):
2)
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testBatchNormGradImpl(self):
x_shape = [7, 5, 4, 6]
param_shape = [6]

1
tensorflow/python/ops/nn_fused_batchnorm_test.py
View File

@ -523,6 +523,7 @@ class BatchNormalizationTest(test.TestCase):
data_format='NHWC',
is_training=is_training)
@test_util.disable_xla('This test never passed for XLA')
def testBatchNormGradShape5(self):
for is_training in [True, False]:
x_shape = [0, 7, 11, 4]

2
tensorflow/python/ops/nn_test.py
View File

@ -41,6 +41,7 @@ from tensorflow.python.ops.nn_impl import _compute_sampled_logits
from tensorflow.python.platform import test as test_lib
@test_util.disable_all_xla("This test never passed for XLA")
class ZeroFractionTest(test_lib.TestCase):
def _ZeroFraction(self, x):
@ -1017,6 +1018,7 @@ class LeakyReluTest(test_lib.TestCase):
class SwishTest(test_lib.TestCase):
@test_util.run_deprecated_v1
@test_util.disable_xla("This test never passed for XLA")
def testValues(self):
np_values = np.array(
[np.linspace(-10.0, 0.0, 100),

2
tensorflow/python/ops/parallel_for/BUILD
View File

@ -114,6 +114,7 @@ cuda_py_test(
"//tensorflow/python:random_ops",
"//tensorflow/python:util",
],
xla_enable_strict_auto_jit = True,
)
cuda_py_test(
@ -171,4 +172,5 @@ cuda_py_test(
"//tensorflow/python/ops/losses",
],
tags = ["optonly"], # Too slow in non-opt mode
xla_enable_strict_auto_jit = True,
)

1
tensorflow/python/ops/parallel_for/control_flow_ops_test.py
View File

@ -251,6 +251,7 @@ class NNTest(PForTestCase):
self._test_loop_fn(loop_fn, 3, loop_fn_dtypes=[dtypes.float32] * 3)
@test_util.disable_xla("This test never passed for XLA")
def test_fused_batch_norm(self):
data_formats = ["NHWC"]
if test.is_gpu_available():

1
tensorflow/python/ops/parallel_for/gradients_test.py
View File

@ -482,6 +482,7 @@ class GradientsTest(test.TestCase):
pfor_jacobian, while_jacobian = create_lstm_batch_jacobian(8, 4, 2)
self.run_and_assert_equal(pfor_jacobian, while_jacobian)
@test_util.disable_xla("This test never passed for XLA")
def test_dynamic_lstm_batch_jacobian(self):
pfor_jacobian, while_gradients = create_dynamic_lstm_batch_jacobian(8, 4, 3)
with session.Session() as sess:

1
tensorflow/python/ops/special_math_ops_test.py
View File

@ -119,6 +119,7 @@ class LBetaTest(test.TestCase):
special_math_ops.lbeta(x).get_shape())
@test_util.run_in_graph_and_eager_modes
@test_util.disable_xla('This test never passed for XLA')
def test_length_1_last_dimension_results_in_one(self):
# If there is only one coefficient, the formula still works, and we get one
# as the answer, always.

23
tensorflow/tensorflow.bzl
View File

@ -1802,8 +1802,17 @@ def tf_py_test(
additional_visibility = [],
kernels = [],
flaky = 0,
xla_enable_strict_auto_jit = False,
xla_enabled = False,
grpc_enabled = False):
"""Create one or more python tests with extra tensorflow dependencies."""
xla_test_true_list = []
# xla_enable_strict_auto_jit is used to run Tensorflow unit tests with all XLA compilable
# kernels compiled with XLA.
if xla_enable_strict_auto_jit:
xla_enabled = True
xla_test_true_list += ["//tensorflow/python:is_xla_test_true"]
if xla_enabled:
additional_deps = additional_deps + tf_additional_xla_deps_py()
if grpc_enabled:
@ -1824,7 +1833,7 @@ def tf_py_test(
deps = [
clean_dep("//tensorflow/python:extra_py_tests_deps"),
clean_dep("//tensorflow/python:gradient_checker"),
] + additional_deps,
] + additional_deps + xla_test_true_list,
)
register_extension_info(
@ -1844,8 +1853,12 @@ def cuda_py_test(
kernels = [],
tags = [],
flaky = 0,
xla_enable_strict_auto_jit = False,
xla_enabled = False,
grpc_enabled = False):
# TODO(b/122522101): Don't ignore xla_enable_strict_auto_jit and enable additional
# XLA tests once enough compute resources are available.
_ignored = [xla_enable_strict_auto_jit]
if main == None:
main = name + ".py"
for config in ["cpu", "gpu"]:
@ -1868,6 +1881,7 @@ def cuda_py_test(
shard_count = shard_count,
tags = test_tags,
xla_enabled = xla_enabled,
xla_enable_strict_auto_jit = False,
)
register_extension_info(
@ -1921,6 +1935,7 @@ def py_tests(
tags = [],
shard_count = 1,
prefix = "",
xla_enable_strict_auto_jit = False,
xla_enabled = False,
grpc_enabled = False):
for src in srcs:
@ -1939,6 +1954,7 @@ def py_tests(
shard_count = shard_count,
tags = tags,
xla_enabled = xla_enabled,
xla_enable_strict_auto_jit = xla_enable_strict_auto_jit,
)
def cuda_py_tests(
@ -1951,8 +1967,12 @@ def cuda_py_tests(
shard_count = 1,
tags = [],
prefix = "",
xla_enable_strict_auto_jit = False,
xla_enabled = False,
grpc_enabled = False):
# TODO(b/122522101): Don't ignore xla_enable_strict_auto_jit and enable additional
# XLA tests once enough compute resources are available.
_ignored = [xla_enable_strict_auto_jit]
test_tags = tags + tf_cuda_tests_tags()
py_tests(
name = name,
@ -1966,6 +1986,7 @@ def cuda_py_tests(
shard_count = shard_count,
tags = test_tags,
xla_enabled = xla_enabled,
xla_enable_strict_auto_jit = False,
)
# Creates a genrule named <name> for running tools/proto_text's generator to