[incubator-mxnet] branch master updated: Decrease success rate to make test more stable (#12092)

[ma...@apache.org]

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marcoabreu pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
     new 787cd08  Decrease success rate to make test more stable (#12092)
787cd08 is described below

commit 787cd08b9849c08b9853d2dea88427983d3fe7d0
Author: Sergey Sokolov <Se...@gmail.com>
AuthorDate: Fri Aug 10 02:57:24 2018 -0700

    Decrease success rate to make test more stable (#12092)
    
    I have added this test back to unit test coverage and decreased success rate even more, to make sure that fails would happen even more rare
---
 tests/python/unittest/test_random.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/tests/python/unittest/test_random.py b/tests/python/unittest/test_random.py
index 43e9608..2d1bf12 100644
--- a/tests/python/unittest/test_random.py
+++ b/tests/python/unittest/test_random.py
@@ -447,20 +447,20 @@ def test_uniform_generator():
             verify_generator(generator=generator_mx_same_seed, buckets=buckets, probs=probs)
 
 @with_seed()
-@unittest.skip('Flaky test, tracked in: https://github.com/apache/incubator-mxnet/issues/9856')
 def test_gamma_generator():
+    success_rate = 0.05
     ctx = mx.context.current_context()
     for dtype in ['float16', 'float32', 'float64']:
         for kappa, theta in [(0.5, 1.0), (1.0, 5.0)]:
             print("ctx=%s, dtype=%s, Shape=%g, Scale=%g:" % (ctx, dtype, kappa, theta))
             buckets, probs = gen_buckets_probs_with_ppf(lambda x: ss.gamma.ppf(x, a=kappa, loc=0, scale=theta), 5)
             generator_mx = lambda x: mx.nd.random.gamma(kappa, theta, shape=x, ctx=ctx, dtype=dtype).asnumpy()
-            verify_generator(generator=generator_mx, buckets=buckets, probs=probs)
+            verify_generator(generator=generator_mx, buckets=buckets, probs=probs, success_rate=success_rate)
             generator_mx_same_seed = \
                 lambda x: np.concatenate(
                     [mx.nd.random.gamma(kappa, theta, shape=x // 10, ctx=ctx, dtype=dtype).asnumpy()
                      for _ in range(10)])
-            verify_generator(generator=generator_mx_same_seed, buckets=buckets, probs=probs)
+            verify_generator(generator=generator_mx_same_seed, buckets=buckets, probs=probs, success_rate=success_rate)
 
 @with_seed()
 def test_exponential_generator():