Comments (3)
Hvass-Labs
commented on August 26, 2024
I'm sorry but I don't understand your question and I cannot find this code in Tutorial 09.
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Caspain
commented on August 26, 2024
well it was lesson 9(video data) it was the one_hot_encoded method return statement.
return np.eye(num_classes)[class_numbers]. Could you explain whats going on here?
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Hvass-Labs
commented on August 26, 2024
It is a fast way of converting class-numbers to one-hot encoded arrays. I think one-hot encoded arrays were explained in one of the early tutorials.
Here's an example:
Python 3.5.2 |Anaconda 4.2.0 (64-bit)| (default, Jul 2 2016, 17:53:06)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> np.eye(10)
array([[ 1., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 1., 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 1., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 1., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 1., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 1., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]])
>>> a = np.eye(10)
>>> a[3]
array([ 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.])
>>> a[5]
array([ 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.])
>>> a[[3,5]]
array([[ 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 1., 0., 0., 0., 0.]])
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Related Issues (20)
- when i was trying to run this code in pycharm it unables to download inception package and it results to an error ImportError: No module named 'inception' so please help me to overcome on this issue HOT 1
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- model.prediction does not match model.evaluation loss error HOT 3
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