I traversed all the use cases in the test, but none of them gave an error.
```
@with_seed()
def test_l2_normalization():
for dtype in ['float16', 'float32', 'float64']:
for mode in ['channel', 'spatial', 'instance']:
nbatch = random.randint(1, 4)
nchannel = random.randint(3, 5)
height = random.randint(4, 6)
check_l2_normalization((nbatch, nchannel, height), mode, dtype)
width = random.randint(5, 7)
check_l2_normalization((nbatch, nchannel, height, width), mode,
dtype)
#test_l2_normalization()
#@with_seed()
def test_l2_normalization2():
for dtype in ['float16', 'float32', 'float64']:
for mode in ['channel', 'spatial', 'instance']:
for nbatch in range(1,5):
for nchannel in range(3,6):
for height in range(4,7):
check_l2_normalization((nbatch, nchannel, height),
mode, dtype)
print((nbatch, nchannel, height), '...ok')
for width in range(5,8):
check_l2_normalization((nbatch, nchannel, height,
width), mode, dtype)
test_l2_normalization()
```
I found this error every time in asnumpy.
This may be a running environment issue? What environment should I use to look
for this bug?
@haojin2 @piiswrong @leezu @anirudh2290 @szha
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https://github.com/apache/incubator-mxnet/pull/12287 ]
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