experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

[XLA:TPU] Add F64 Cosine.

Browse Source 
Now, F64 Stateless Random Normal should be supported on TPU.

PiperOrigin-RevId: 306355714
Change-Id: Ib6dee1ddb66c92893887aa1ad2d5c37c17e945c9
This commit is contained in:
Anudhyan Boral 2020-04-13 18:52:10 -07:00 committed by TensorFlower Gardener
parent 162ce62eed
commit 258d16bc66
1 changed files with 22 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

27
tensorflow/compiler/tests/unary_ops_test.py
View File

@ -151,20 +151,37 @@ class UnaryOpsTest(xla_test.XLATestCase):
def testSin(self):
for dtype in self.float_types - {dtypes.bfloat16.as_numpy_dtype}:
tol = 1e-3 if dtype == np.float32 else 1e-10
tol = 1e-6 if dtype == np.float32 else 1e-12
x = np.linspace(-4 * np.pi, 4 * np.pi, num=1000, dtype=dtype)
x = np.linspace(-4 * np.e, 4 * np.e, num=1000, dtype=dtype)
self._assertOpOutputMatchesExpected(
math_ops.sin, x, expected=np.sin(x), rtol=tol, atol=tol)
x = np.linspace(0., 2.71828e-30, num=1000, dtype=dtype)
x = np.linspace(0., np.e * 1e-30, num=1000, dtype=dtype)
self._assertOpOutputMatchesExpected(
math_ops.sin, x, expected=np.sin(x), rtol=tol, atol=tol)
if dtype == np.float64:
x = np.linspace(0., 3.141592e8, num=1000, dtype=dtype)
x = np.linspace(0., np.e * 1e8, num=1000, dtype=dtype)
self._assertOpOutputMatchesExpected(
math_ops.sin, x, expected=np.sin(x), rtol=1e-5, atol=1e-5)
math_ops.sin, x, expected=np.sin(x), rtol=tol, atol=1e-5)
def testCos(self):
for dtype in self.float_types - {dtypes.bfloat16.as_numpy_dtype}:
tol = 1e-6 if dtype == np.float32 else 1e-12
x = np.linspace(-4 * np.e, 4 * np.e, num=1000, dtype=dtype)
self._assertOpOutputMatchesExpected(
math_ops.cos, x, expected=np.cos(x), rtol=tol, atol=tol)
x = np.linspace(0., np.e * 1e-30, num=1000, dtype=dtype)
self._assertOpOutputMatchesExpected(
math_ops.cos, x, expected=np.cos(x), rtol=tol, atol=tol)
if dtype == np.float64:
x = np.linspace(0., np.e * 1e8, num=1000, dtype=dtype)
self._assertOpOutputMatchesExpected(
math_ops.cos, x, expected=np.cos(x), rtol=tol, atol=1e-5)
def testFloatOps(self):
for dtype in self.float_types: