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Assert closeness of output values instead of equality in layout optimizer tests

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using convolutions

Convolution output may differ across convolution algorithms and is not guaranteed to match exactly.

PiperOrigin-RevId: 205276671
This commit is contained in:
Smit Hinsu 2018-07-19 11:49:44 -07:00 committed by TensorFlower Gardener
parent 8571b4f3d2
commit 3d6c8b8aae
1 changed files with 1 additions and 1 deletions
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tensorflow/python/grappler/layout_optimizer_test.py
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@ -1340,7 +1340,7 @@ class LayoutOptimizerTest(test.TestCase):
expected_num_transposes = 2 expected_num_transposes = 2
self.assertEqual(expected_num_transposes, num_transposes) self.assertEqual(expected_num_transposes, num_transposes)
self._assert_trans_nhwc_to_nchw('Conv2D-0', nodes) self._assert_trans_nhwc_to_nchw('Conv2D-0', nodes)
self.assertAllEqual(output_val_ref, output_val) self.assertAllClose(output_val_ref, output_val, atol=1e-3)
def testLoop(self): def testLoop(self):
if test.is_gpu_available(cuda_only=True): if test.is_gpu_available(cuda_only=True):