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| author | discus0434 <discus0434@gmail.com> | 2022-10-18 16:03:58 +0000 |
|---|---|---|
| committer | discus0434 <discus0434@gmail.com> | 2022-10-18 16:03:58 +0000 |
| commit | e40ba281f1b419cf99552962ea01d87d699840a5 (patch) | |
| tree | abdd39d18d8e07f4e2e552f56459676c67b4e600 | |
| parent | 7f2095c6c8db82a5c9cd7c7177f6ba856a2cc676 (diff) | |
| download | stable-diffusion-webui-gfx803-e40ba281f1b419cf99552962ea01d87d699840a5.tar.gz stable-diffusion-webui-gfx803-e40ba281f1b419cf99552962ea01d87d699840a5.tar.bz2 stable-diffusion-webui-gfx803-e40ba281f1b419cf99552962ea01d87d699840a5.zip | |
update
| -rw-r--r-- | modules/hypernetworks/hypernetwork.py | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index c5835bce..082165f4 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -309,7 +309,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log with torch.autocast("cuda"):
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)
loss = shared.sd_model(x, c)[0]
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), {
"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:
|