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()