Follow-up the implementation #7
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Contributor
fperdigon
commented
May 22, 2019
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fperdigon
commented
- label_guessin function added
- to_categorical function added
- Modify the MixUp according to the MixMatch paper
- Fix some small error
- Adding some comments
- Specify in the README.md that the implementation is not finished
The MixUp used the paper is a slightly modified version to avoid problems with the SSL loss. Also, the name of the function was changed to mixup_mod to be explicit that is a modified version.
Adding Label Guessing function This function converts the NumPy array in Pytorch tensors. Then predict the labels. The predictions average is returned in NumPy array type, this helps to keep all variables inside MixMatch in NumPy type. The function was added in the mixmatch function.
Normally the PyTorch labels for classification are in integer numbers associated with classes. For the MixMatch algorithm, the labels need to be in one hot format. The to_categorical function was taken from Keras code, is able to handle batches. num_clases=10 for future CIFAR test. Inside of the algorithm y is converted to one hot encode format. At the end of the MixMatch phase, the labels p and q are converted back to the natural classes format in PyTorch
- Fix the indices generation - Wy must be the concatenation of Uy and y (before qb and y, this generated a size mismatch with Ux) - Adding some comments
Adding that the project is not finished in the README.md
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