diff options
Diffstat (limited to 'tensorflow/compiler/tests/adagrad_test.py')
| -rw-r--r-- | tensorflow/compiler/tests/adagrad_test.py | 18 |
1 files changed, 12 insertions, 6 deletions
diff --git a/tensorflow/compiler/tests/adagrad_test.py b/tensorflow/compiler/tests/adagrad_test.py index a5c5885b42..9a93b32164 100644 --- a/tensorflow/compiler/tests/adagrad_test.py +++ b/tensorflow/compiler/tests/adagrad_test.py @@ -49,9 +49,11 @@ class AdagradOptimizerTest(XLATestCase): ada_update.run() # Validate updated params self.assertAllCloseAccordingToType( - np.array([-1.6026098728179932, -0.6026098728179932]), var0.eval()) + np.array([-1.6026098728179932, -0.6026098728179932]), var0.eval(), + float_rtol=1e-5) self.assertAllCloseAccordingToType( - np.array([2.715679168701172, 3.715679168701172]), var1.eval()) + np.array([2.715679168701172, 3.715679168701172]), var1.eval(), + float_rtol=1e-5) def testTensorLearningRate(self): for dtype in self.float_types: @@ -73,9 +75,11 @@ class AdagradOptimizerTest(XLATestCase): ada_update.run() # Validate updated params self.assertAllCloseAccordingToType( - np.array([-1.6026098728179932, -0.6026098728179932]), var0.eval()) + np.array([-1.6026098728179932, -0.6026098728179932]), var0.eval(), + float_rtol=1e-5) self.assertAllCloseAccordingToType( - np.array([2.715679168701172, 3.715679168701172]), var1.eval()) + np.array([2.715679168701172, 3.715679168701172]), var1.eval(), + float_rtol=1e-5) def testSharing(self): for dtype in self.float_types: @@ -107,9 +111,11 @@ class AdagradOptimizerTest(XLATestCase): ada_update1.run() # Validate updated params (the same as with only 1 Adagrad). self.assertAllCloseAccordingToType( - np.array([-1.6026098728179932, -0.6026098728179932]), var0.eval()) + np.array([-1.6026098728179932, -0.6026098728179932]), var0.eval(), + float_rtol=1e-5) self.assertAllCloseAccordingToType( - np.array([2.715679168701172, 3.715679168701172]), var1.eval()) + np.array([2.715679168701172, 3.715679168701172]), var1.eval(), + float_rtol=1e-5) if __name__ == "__main__": |