[incubator-mxnet] branch master updated: Fixes test_operator_gpu.test_multinomial_generator (#14475)

[wk...@apache.org]

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wkcn 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 a01bdee  Fixes test_operator_gpu.test_multinomial_generator (#14475)
a01bdee is described below

commit a01bdee4beafd1a5caf0cf11be492879ebce417d
Author: Jake Lee <gs...@gmail.com>
AuthorDate: Thu Mar 21 11:39:29 2019 +0800

    Fixes test_operator_gpu.test_multinomial_generator (#14475)
    
    * adjust the success rate
    
    * add comments
---
 tests/python/unittest/test_random.py | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/tests/python/unittest/test_random.py b/tests/python/unittest/test_random.py
index d1340c4..2f5aad2 100644
--- a/tests/python/unittest/test_random.py
+++ b/tests/python/unittest/test_random.py
@@ -641,15 +641,20 @@ def test_multinomial_generator():
         quantized_probs = quantize_probs(probs, dtype)
         generator_mx = lambda x: mx.nd.random.multinomial(data=mx.nd.array(quantized_probs, ctx=ctx, dtype=dtype),
                                                           shape=x).asnumpy()
+        # success_rate was set to 0.15 since PR #13498 and became flaky
+        # both of previous issues(#14457, #14158) failed with success_rate 0.25
+        # In func verify_generator inside test_utilis.py
+        # it raise the error when success_num(1) < nrepeat(5) * success_rate(0.25)
+        # by changing the 0.25 -> 0.2 solve these edge case but still have strictness
         verify_generator(generator=generator_mx, buckets=buckets, probs=quantized_probs,
-                         nsamples=samples, nrepeat=trials)
+                         nsamples=samples, nrepeat=trials, success_rate=0.20)
         generator_mx_same_seed = \
             lambda x: np.concatenate(
                 [mx.nd.random.multinomial(data=mx.nd.array(quantized_probs, ctx=ctx, dtype=dtype),
                                                           shape=x // 10).asnumpy()
                  for _ in range(10)])
         verify_generator(generator=generator_mx_same_seed, buckets=buckets, probs=quantized_probs,
-                         nsamples=samples, nrepeat=trials)
+                         nsamples=samples, nrepeat=trials, success_rate=0.20)
 
 
 @with_seed()