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[ROCm] Fix for ROCm CSB breakage - 200608

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The test `//tensorflow/python/ops/numpy_ops:np_math_ops_test_gpu` started failing on Friday (200605), with the following error

```
=====================================================================
FAIL: testExp (__main__.MathTest)
testExp (__main__.MathTest)
----------------------------------------------------------------------
Traceback (most recent call last):
...
...
AssertionError:
Arrays are not almost equal to 7 decimals

Mismatched elements: 1 / 2 (50%)
Max absolute difference: 4.76837158e-07
Max relative difference: 6.45328909e-08
 x: array([ 7.3890557, 20.085537 ])
 y: array([ 7.3890562, 20.085537 ])

----------------------------------------------------------------------
Ran 19 tests in 24.663s

FAILED (failures=1, skipped=1)
================================================================================

```

This is a new unit test introduced by the commit 84c796966b

The fix is to drop the relative tolerance down to 1e-6 (from the default of 1e-7). This should be okay since numerous other TF unit tests also use the same value for relative tolerance.

Note that this commit also changes the check call from `assert_almost_equal` to `assert_allclose`, to be able to specifyt eh relative tolerance
This commit is contained in:
Deven Desai 2020-06-08 17:13:59 +00:00
parent dab7b46024
commit 8abf495b5f
1 changed files with 1 additions and 1 deletions
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tensorflow/python/ops/numpy_ops/np_math_ops_test.py
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@ -159,7 +159,7 @@ class MathTest(test.TestCase, parameterized.TestCase):
actual.shape, expected.shape, actual.shape, expected.shape,
'Shape mismatch.\nActual: {}\nExpected: {}\n{}'.format( 'Shape mismatch.\nActual: {}\nExpected: {}\n{}'.format(
actual.shape, expected.shape, msg)) actual.shape, expected.shape, msg))
np.testing.assert_almost_equal(actual.tolist(), expected.tolist()) np.testing.assert_allclose(actual.tolist(), expected.tolist(), rtol=1e-6)
def testArgsort(self): def testArgsort(self):
self._testUnaryOp(np_math_ops.argsort, np.argsort, 'argsort') self._testUnaryOp(np_math_ops.argsort, np.argsort, 'argsort')