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Posted to issues@mxnet.apache.org by GitBox <gi...@apache.org> on 2021/02/05 20:43:55 UTC
[GitHub] [incubator-mxnet] DNXie opened a new issue #19852: `mxnet.gluon.nn.instancenorm` output NaN
DNXie opened a new issue #19852:
URL: https://github.com/apache/incubator-mxnet/issues/19852
## Description
`mxnet.gluon.nn.instancenorm` output NaN
## To Reproduce
~~~python
import mxnet
layer=mxnet.gluon.nn.InstanceNorm()
layer.initialize()
input=mxnet.nd.array([[[[ 1.4918449e+38],[ 9.0072335e+37],[-1.3146734e+38],[ 3.0568930e+38]]]])
out=layer(input)
print(out)
~~~
Output:
~~~python
[[[[nan]
[nan]
[nan]
[nan]]]]
<NDArray 1x1x4x1 @cpu(0)>
~~~
## Environment
OS: ubuntu 18.04
Python: 3.7.6
pip: 20.0.2
numpy: 1.18.5
mxnet: 1.6.0
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[GitHub] [incubator-mxnet] TristonC commented on issue #19852: `mxnet.gluon.nn.instancenorm` output NaN
Posted by GitBox <gi...@apache.org>.
TristonC commented on issue #19852:
URL: https://github.com/apache/incubator-mxnet/issues/19852#issuecomment-774373100
@DNXie It runs into numerical overflow for your case as entries in your ndarry are 'big' in terms of float32 representation. You may need to perform mathematical treatment for the input before doing the InstanceNorm, such as dividing every element by its max entry.
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