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discus0434 2022-10-19 01:03:58 +09:00
parent 7f2095c6c8
commit e40ba281f1
1 changed files with 2 additions and 2 deletions
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4
modules/hypernetworks/hypernetwork.py
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@ -309,7 +309,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
with torch.autocast("cuda"): with torch.autocast("cuda"):
c = stack_conds([entry.cond for entry in entries]).to(devices.device) c = stack_conds([entry.cond for entry in entries]).to(devices.device)
c = torch.vstack([entry.cond for entry in entries]).to(devices.device) # c = torch.vstack([entry.cond for entry in entries]).to(devices.device)
x = torch.stack([entry.latent for entry in entries]).to(devices.device) x = torch.stack([entry.latent for entry in entries]).to(devices.device)
loss = shared.sd_model(x, c)[0] loss = shared.sd_model(x, c)[0]
del x del x
@ -331,7 +331,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), { textual_inversion.write_loss(log_directory, "hypernetwork_loss.csv", hypernetwork.step, len(ds), {
"loss": f"{mean_loss:.7f}", "loss": f"{mean_loss:.7f}",
"learn_rate": f"{scheduler.learn_rate:.7f}" "learn_rate": scheduler.learn_rate
}) })
if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: if hypernetwork.step > 0 and images_dir is not None and hypernetwork.step % create_image_every == 0: