More fixes to corrupt_fea
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@ -177,10 +177,7 @@ class SRGANModel(BaseModel):
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self.use_corrupted_feature_input = train_opt['corrupted_feature_input'] if 'corrupted_feature_input' in train_opt.keys() else False
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if self.use_corrupted_feature_input:
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logger.info("Corrupting inputs into the feature network..")
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self.feature_corruptor = GaussianBlur()
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else:
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logger.info("Using normal inputs into feature network..")
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print(train_opt)
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self.feature_corruptor = GaussianBlur().to(self.device)
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self.netF = networks.define_F(use_bn=False).to(self.device)
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self.lr_netF = None
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if 'lr_fea_path' in train_opt.keys():
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@ -502,8 +499,6 @@ class SRGANModel(BaseModel):
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elif self.use_corrupted_feature_input:
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cor_Pix = F.interpolate(self.feature_corruptor(pix), size=var_L.shape[2:])
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real_fea = self.netF(cor_Pix).detach()
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if step % 50 == 0:
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utils.save_image(cor_Pix.detach().cpu(), "corrupted_pix.png")
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else:
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real_fea = self.netF(pix).detach()
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if self.use_corrupted_feature_input:
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@ -32,7 +32,7 @@ def init_dist(backend='nccl', **kwargs):
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def main():
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#### options
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parser = argparse.ArgumentParser()
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_mi1_spsr_switched2.yml')
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../experiments/finetune_imgset_spsr_switched2_xlbatch_limfeat.yml')
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parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none',
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help='job launcher')
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parser.add_argument('--local_rank', type=int, default=0)
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