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- from fastai.vision import *
-
-
- class FeatureLoss(nn.Module):
- def __init__(self, m_feat, layer_ids, layer_wgts):
- super().__init__()
- self.m_feat = m_feat
- self.loss_features = [self.m_feat[i] for i in layer_ids]
- self.hooks = hook_outputs(self.loss_features, detach=False)
- self.wgts = layer_wgts
- self.metric_names = ['pixel', ] + [f'feat_{i}' for i in range(len(layer_ids))
- ] + [f'gram_{i}' for i in range(len(layer_ids))]
-
- def make_features(self, x, clone=False):
- self.m_feat(x)
- return [(o.clone() if clone else o) for o in self.hooks.stored]
-
- def forward(self, input, target):
- out_feat = self.make_features(target, clone=True)
- in_feat = self.make_features(input)
- self.feat_losses = [base_loss(input, target)]
- self.feat_losses += [base_loss(f_in, f_out) * w
- for f_in, f_out, w in zip(in_feat, out_feat, self.wgts)]
- self.feat_losses += [base_loss(gram_matrix(f_in), gram_matrix(f_out)) * w ** 2 * 5e3
- for f_in, f_out, w in zip(in_feat, out_feat, self.wgts)]
- self.metrics = dict(zip(self.metric_names, self.feat_losses))
- return sum(self.feat_losses)
-
- def __del__(self): self.hooks.remove()
-
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