4d0e2b25a3064079923e48729a0568bbae636d88,torchbearer/callbacks/imaging/inside_cnns.py,ClassAppearanceModel,on_batch,#ClassAppearanceModel#Any#,96

Before Change

        targets_hot = self._targets_hot(state)

        to_prob = (lambda x: x.exp()) if self.prob_key is None else (lambda x: x)
        key = self.logit_key if self.prob_key is None else self.prob_key

        model = _CAMWrapper(self.input_size, state[torchbearer.MODEL])
        trial = torchbearer.Trial(model, self.optimizer_factory(filter(lambda p: p.requires_grad, [model.input_batch])),
                                  _cam_loss(key, to_prob, targets_hot, self.decay))

After Change

        if training:
            state[torchbearer.MODEL].train()

        return model.input_image.sigmoid()

Instances