nodes/city96-SD-Latent-Upscaler
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v2.1 models

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City
2023-08-19 12:40:06 +02:00
parent 19eec00743
commit e0f42917d5
2 changed files with 4 additions and 3 deletions
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comfy_latent_upscaler.py
+1 -1
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@@ -9,7 +9,7 @@ class Upscaler(nn.Module):
Basic NN layout, ported from: Basic NN layout, ported from:
https://github.com/city96/SD-Latent-Upscaler/blob/main/upscaler.py https://github.com/city96/SD-Latent-Upscaler/blob/main/upscaler.py
""" """
version = 2.0 # network revision version = 2.1 # network revision
def head(self): def head(self):
return [ return [
nn.Conv2d(self.chan, self.size, kernel_size=self.krn, padding=self.pad), nn.Conv2d(self.chan, self.size, kernel_size=self.krn, padding=self.pad),
train.py
+3 -2
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@@ -112,8 +112,8 @@ if __name__ == "__main__":
eval_src = torch.from_numpy(np.load(f"test_{args.ver}_{args.res}px.npy")).to(target_dev) eval_src = torch.from_numpy(np.load(f"test_{args.ver}_{args.res}px.npy")).to(target_dev)
eval_dst = torch.from_numpy(np.load(f"test_{args.ver}_{dst_res}px.npy")).to(target_dev) eval_dst = torch.from_numpy(np.load(f"test_{args.ver}_{dst_res}px.npy")).to(target_dev)
else: else:
eval_src = dataset[0][0] eval_src = torch.unsqueeze(dataset[0][0],0)
eval_dst = dataset[0][1] eval_dst = torch.unsqueeze(dataset[0][1],0)
model = Upscaler(args.fac) model = Upscaler(args.fac)
if args.resume: if args.resume:
@@ -131,6 +131,7 @@ if __name__ == "__main__":
total_steps=int(args.steps/args.bs), total_steps=int(args.steps/args.bs),
max_lr=float(args.lr)/args.bs, max_lr=float(args.lr)/args.bs,
pct_start=0.015, pct_start=0.015,
final_div_factor=2500,
) )
# scaler = torch.cuda.amp.GradScaler() # scaler = torch.cuda.amp.GradScaler()
progress = tqdm(total=args.steps) progress = tqdm(total=args.steps)