[GitHub] leleamol edited a comment on issue #12869: Python trained model gives different features set in C++

[GitBox <gi...@apache.org>]

leleamol edited a comment on issue #12869: Python trained model gives different features set in C++
URL: https://github.com/apache/incubator-mxnet/issues/12869#issuecomment-431910422
 
 
   With my test program I was able to get the output of float vector of 512. Without using sklearn.preprocessing.normalize on that output (similar to what was done in the test python script),  the maximum accuracy was reported to be 2.7216 at index 84.   The rest of the entries in 512D vector were 0.03412.  ( I have used the same image as that of test.py)
   
   I did not normalize the image before running forward pass.
   If this helps, I can share the code of my example.

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