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Convert linspace tests to parameterized tests

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Helps with TSAN timeouts.

PiperOrigin-RevId: 333195144
Change-Id: Iceb62706c9664ef14cb78f59919631af81e30389
This commit is contained in:
Akshay Modi 2020-09-22 17:36:53 -07:00 committed by TensorFlower Gardener
parent 070efb9ebf
commit 4c71606397
2 changed files with 25 additions and 19 deletions
tensorflow/python
BUILD
ops
math_ops_linspace_test.py

1
tensorflow/python/BUILD
View File

@ -5282,7 +5282,6 @@ cuda_py_test(
python_version = "PY3",
tags = [
"no_windows_gpu",
"notsan", # b/168815578
],
deps = [
":framework_for_generated_wrappers",

43
tensorflow/python/ops/math_ops_linspace_test.py
View File

@ -21,8 +21,8 @@ from __future__ import print_function
# Using distutils.version.LooseVersion was resulting in an error, so importing
# directly.
from distutils.version import LooseVersion # pylint: disable=g-importing-member
import itertools
from absl.testing import parameterized
import numpy as np
from tensorflow.python.framework import test_util
@ -31,29 +31,36 @@ from tensorflow.python.platform import googletest
@test_util.run_all_in_graph_and_eager_modes
class LinspaceTest(test_util.TensorFlowTestCase):
class LinspaceTest(test_util.TensorFlowTestCase, parameterized.TestCase):
def testLinspaceBroadcasts(self):
# pylint: disable=g-complex-comprehension
@parameterized.parameters([
{
"start_shape": start_shape,
"stop_shape": stop_shape,
"dtype": dtype,
"num": num
}
for start_shape in [(), (2,), (2, 2)]
for stop_shape in [(), (2,), (2, 2)]
for dtype in [np.float64, np.int64]
for num in [0, 1, 2, 20]
])
# pylint: enable=g-complex-comprehension
def testLinspaceBroadcasts(self, start_shape, stop_shape, dtype, num):
if LooseVersion(np.version.version) < LooseVersion("1.16.0"):
self.skipTest("numpy doesn't support axes before version 1.16.0")
shapes = [(), (2,), (2, 2)]
ndims = max(len(start_shape), len(stop_shape))
for axis in range(-ndims, ndims):
start = np.ones(start_shape, dtype)
stop = 10 * np.ones(stop_shape, dtype)
types = [np.float64, np.int64]
np_ans = np.linspace(start, stop, num, axis=axis)
tf_ans = self.evaluate(
math_ops.linspace_nd(start, stop, num, axis=axis))
for start_shape, stop_shape in itertools.product(shapes, repeat=2):
for num in [0, 1, 2, 20]:
ndims = max(len(start_shape), len(stop_shape))
for axis in range(-ndims, ndims):
for dtype in types:
start = np.ones(start_shape, dtype)
stop = 10 * np.ones(stop_shape, dtype)
np_ans = np.linspace(start, stop, num, axis=axis)
tf_ans = self.evaluate(
math_ops.linspace_nd(start, stop, num, axis=axis))
self.assertAllClose(np_ans, tf_ans)
self.assertAllClose(np_ans, tf_ans)
if __name__ == "__main__":