aaronmarkham opened a new issue #12417: test_operator.test_l2_normalization 
failure in CI
URL: https://github.com/apache/incubator-mxnet/issues/12417
 
 
   The PR is unrelated to anything that would have failed this test...
   
   
http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/incubator-mxnet/detail/PR-12413/1/pipeline
   
   ```
   ======================================================================
   
   FAIL: test_operator.test_l2_normalization
   
   ----------------------------------------------------------------------
   
   Traceback (most recent call last):
   
     File "C:\Anaconda3\envs\py2\lib\site-packages\nose\case.py", line 197, in 
runTest
   
       self.test(*self.arg)
   
     File 
"C:\jenkins_slave\workspace\ut-python-gpu\tests\python\unittest\common.py", 
line 172, in test_new
   
       orig_test(*args, **kwargs)
   
     File 
"C:\jenkins_slave\workspace\ut-python-gpu\tests\python\unittest\test_operator.py",
 line 3134, in test_l2_normalization
   
       check_l2_normalization((nbatch, nchannel, height, width), mode, dtype)
   
     File 
"C:\jenkins_slave\workspace\ut-python-gpu\tests\python\unittest\test_operator.py",
 line 3120, in check_l2_normalization
   
       check_numeric_gradient(out, [in_data], numeric_eps=1e-3, rtol=1e-2, 
atol=1e-3)
   
     File 
"C:\jenkins_slave\workspace\ut-python-gpu\windows_package\python\mxnet\test_utils.py",
 line 912, in check_numeric_gradient
   
       ("NUMERICAL_%s"%name, "BACKWARD_%s"%name))
   
     File 
"C:\jenkins_slave\workspace\ut-python-gpu\windows_package\python\mxnet\test_utils.py",
 line 491, in assert_almost_equal
   
       raise AssertionError(msg)
   
   AssertionError: 
   
   Items are not equal:
   
   Error 1.721498 exceeds tolerance rtol=0.010000, atol=0.001000.  Location of 
maximum error:(1, 0, 2, 1), a=-0.194527, b=-0.199686
   
    NUMERICAL_data: array([[[[  1.49086118,   0.15851855,   0.26511028, ...,   
0.04867464,
   
               1.2716279 ,  -0.13297796],
   
            [  0.62356889,  -0.54586679,   0.78976154, ...,   1.01109409,...
   
    BACKWARD_data: array([[[[  1.49098313,   0.15851827,   0.26509097, ...,   
0.04858097,
   
               1.27164507,  -0.13300258],
   
            [  0.62362021,  -0.54588604,   0.78978229, ...,   1.01112676,...
   
   -------------------- >> begin captured logging << --------------------
   
   common: INFO: Setting test np/mx/python random seeds, use 
MXNET_TEST_SEED=2040851487 to reproduce.
   
   --------------------- >> end captured logging << ---------------------
   
   ```

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