# How to deal with isprobvec(p) error?

**URL:** <https://discourse.julialang.org/t/how-to-deal-with-isprobvec-p-error/36911>\
**Category:** General Usage\
**Created:** [April 2, 2020, 4:39pm UTC](https://discourse.julialang.org/t/how-to-deal-with-isprobvec-p-error/36911 "2020-04-02T16:39:06Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![DeepQ](https://avatars.discourse-cdn.com/v4/letter/d/2bfe46/32.png) [@DeepQ](https://discourse.julialang.org/u/DeepQ)\
**Post date:** [April 2, 2020, 4:39pm UTC](https://discourse.julialang.org/t/how-to-deal-with-isprobvec-p-error/36911/1 "2020-04-02T16:39:06Z")

</div>

I’ve written a neural network using Knet library and I am trying to use the normalized output of the neural network as a density function. The problem is when I use ReLU as the activation function of the neural net and apply column-wise normalization to the output, Julia throws “isprobvec( p) is not satified” error. ReLU always returns zero or a positive number which isn’t the problem. I cannot understand what the cause of error is.