Large variety of nuanced fixes to the U-Nets #8
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The whole idea of these changes is to remove assumption that you're only trying to predict one class (where multi-class cases automatically go for 'softmax'), which is simply not true. Although, this wasn't necessary for this project's goals, it's a solid fix to make the code more generalizable and make more sense. # Changes * Now, can specify out_act, the output activation function for the U-Nets * Removed self._build_predictor because it's not that useful considering how this case is only for 2D images. * Updated documentation
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The whole idea of these changes is to remove assumption that you're only trying to predict one class (where multi-class cases automatically go for 'softmax'), which is simply not true. Although, this wasn't necessary for this project's goals, it's a solid fix to make the code more generalizable and make more sense.
Changes
out_act, the output activation function for the U-Netsself._build_predictorbecause it's not that useful considering how this case is only for 2D images.n_labelsargument toSimpleUNet