(self)
| 159 | return -(torch.log_softmax(prediction, dim=1) * target).sum(1) |
| 160 | |
| 161 | def set_transforms(self): |
| 162 | if self.use_augmentation: |
| 163 | self.transforms = Transforms(self.augmentation, image_shape=(self.obs_shape[1], self.obs_shape[2])) |
| 164 | |
| 165 | def transform(self, images): |
| 166 | return self.transforms.transform(images) |