experiments/STT-tensorflow
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Enable disabled clip_by_value tests

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Most of the disabled tests were trying to test with int8 & uint16 which
is not supported by the Minimum and Maximum kernel.

PiperOrigin-RevId: 314737076
Change-Id: Iee39aae6d95a9a7f18bdcde5a406e60c70466cb6
This commit is contained in:
Gaurav Jain 2020-06-04 08:52:33 -07:00 committed by TensorFlower Gardener
parent 90fdbf3965
commit 3897e02fc9
1 changed files with 34 additions and 13 deletions
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47
tensorflow/python/kernel_tests/clip_ops_test.py
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@ -34,7 +34,8 @@ from tensorflow.python.platform import test
class ClipTest(test.TestCase): class ClipTest(test.TestCase):
def DISABLED_testClipByValueGradient(self): @test_util.run_deprecated_v1
def testClipByValueGradient(self):
inputs = constant_op.constant([1.0, 2.0, 3.0, 4.0], dtype=dtypes.float32) inputs = constant_op.constant([1.0, 2.0, 3.0, 4.0], dtype=dtypes.float32)
outputs_1 = clip_ops.clip_by_value(inputs, 0.5, 3.5) outputs_1 = clip_ops.clip_by_value(inputs, 0.5, 3.5)
min_val = constant_op.constant([0.5, 0.5, 0.5, 0.5], dtype=dtypes.float32) min_val = constant_op.constant([0.5, 0.5, 0.5, 0.5], dtype=dtypes.float32)
@ -61,10 +62,15 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans, tf_ans) self.assertAllClose(np_ans, tf_ans)
# [Tensor, Scalar, Scalar] # [Tensor, Scalar, Scalar]
def DISABLED_testClipByValue0Type(self): def testClipByValue0Type(self):
for dtype in [ for dtype in [
dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int8, dtypes.float16,
dtypes.int16, dtypes.int32, dtypes.int64, dtypes.uint8, dtypes.uint16 dtypes.float32,
dtypes.float64,
dtypes.int16,
dtypes.int32,
dtypes.int64,
dtypes.uint8,
]: ]:
with self.cached_session(use_gpu=True): with self.cached_session(use_gpu=True):
x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype) x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype)
@ -77,10 +83,15 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans, tf_ans) self.assertAllClose(np_ans, tf_ans)
# [Tensor, Tensor, Scalar] # [Tensor, Tensor, Scalar]
def DISABLED_testClipByValue1Type(self): def testClipByValue1Type(self):
for dtype in [ for dtype in [
dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int8, dtypes.float16,
dtypes.int16, dtypes.int32, dtypes.int64, dtypes.uint8, dtypes.uint16 dtypes.float32,
dtypes.float64,
dtypes.int16,
dtypes.int32,
dtypes.int64,
dtypes.uint8,
]: ]:
with self.cached_session(use_gpu=True): with self.cached_session(use_gpu=True):
x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype) x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype)
@ -94,10 +105,15 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans, tf_ans) self.assertAllClose(np_ans, tf_ans)
# [Tensor, Scalar, Tensor] # [Tensor, Scalar, Tensor]
def DISABLED_testClipByValue2Type(self): def testClipByValue2Type(self):
for dtype in [ for dtype in [
dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int8, dtypes.float16,
dtypes.int16, dtypes.int32, dtypes.int64, dtypes.uint8, dtypes.uint16 dtypes.float32,
dtypes.float64,
dtypes.int16,
dtypes.int32,
dtypes.int64,
dtypes.uint8,
]: ]:
with self.cached_session(use_gpu=True): with self.cached_session(use_gpu=True):
x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype) x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype)
@ -111,10 +127,15 @@ class ClipTest(test.TestCase):
self.assertAllClose(np_ans, tf_ans) self.assertAllClose(np_ans, tf_ans)
# [Tensor, Tensor, Tensor] # [Tensor, Tensor, Tensor]
def DISABLED_testClipByValue3Type(self): def testClipByValue3Type(self):
for dtype in [ for dtype in [
dtypes.float16, dtypes.float32, dtypes.float64, dtypes.int8, dtypes.float16,
dtypes.int16, dtypes.int32, dtypes.int64, dtypes.uint8, dtypes.uint16 dtypes.float32,
dtypes.float64,
dtypes.int16,
dtypes.int32,
dtypes.int64,
dtypes.uint8,
]: ]:
with self.cached_session(use_gpu=True): with self.cached_session(use_gpu=True):
x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype) x = constant_op.constant([1, 2, 3, 4, 5, 6], shape=[2, 3], dtype=dtype)