Adding optional parameter activation_dtype to models #327
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As I mentioned on issue #323 , when using mixed_precision, the training does not converge when softmax conversion is also converted. So, to overcome this problem, I've create a parameter activation_dtype that allows user to set the data type of the activations.
I've modified all models and also the EfficientNet ones (I'll pull request the changes to the other repository).
I've tested mixed precision training with the proposed changes and all went well. I've also tested training the normal way and my changes did not break anything, also all unittests passed.
I've also updated the requirements to include noisy students weights to segmentation_models using EfficientNet.
Please feel free to suggest any changes to this pull request, I just want to contribute to this great project.