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| author | AUTOMATIC <16777216c@gmail.com> | 2023-05-13 08:16:37 +0300 |
|---|---|---|
| committer | AUTOMATIC <16777216c@gmail.com> | 2023-05-13 08:16:37 +0300 |
| commit | b08500cec8a791ef20082628b49b17df833f5dda (patch) | |
| tree | 2d09f3ca93139f082b88463f3a2a43a4ac45526f /modules/models/diffusion | |
| parent | 5ab7f213bec2f816f9c5644becb32eb72c8ffb89 (diff) | |
| parent | 231562ea13e4f697953bdbabd6b76b22a88c587b (diff) | |
Merge branch 'release_candidate'
Diffstat (limited to 'modules/models/diffusion')
| -rw-r--r-- | modules/models/diffusion/ddpm_edit.py | 4 | ||||
| -rw-r--r-- | modules/models/diffusion/uni_pc/uni_pc.py | 4 |
2 files changed, 4 insertions, 4 deletions
diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index f3d49c44..f880bc3c 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -223,7 +223,7 @@ class DDPM(pl.LightningModule): for k in keys: for ik in ignore_keys: if k.startswith(ik): - print("Deleting key {} from state_dict.".format(k)) + print(f"Deleting key {k} from state_dict.") del sd[k] missing, unexpected = self.load_state_dict(sd, strict=False) if not only_model else self.model.load_state_dict( sd, strict=False) @@ -386,7 +386,7 @@ class DDPM(pl.LightningModule): _, loss_dict_no_ema = self.shared_step(batch) with self.ema_scope(): _, loss_dict_ema = self.shared_step(batch) - loss_dict_ema = {key + '_ema': loss_dict_ema[key] for key in loss_dict_ema} + loss_dict_ema = {f"{key}_ema": loss_dict_ema[key] for key in loss_dict_ema} self.log_dict(loss_dict_no_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True) self.log_dict(loss_dict_ema, prog_bar=False, logger=True, on_step=False, on_epoch=True) diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index eb5f4e76..11b330bc 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -94,7 +94,7 @@ class NoiseScheduleVP: """ if schedule not in ['discrete', 'linear', 'cosine']: - raise ValueError("Unsupported noise schedule {}. The schedule needs to be 'discrete' or 'linear' or 'cosine'".format(schedule)) + raise ValueError(f"Unsupported noise schedule {schedule}. The schedule needs to be 'discrete' or 'linear' or 'cosine'") self.schedule = schedule if schedule == 'discrete': @@ -469,7 +469,7 @@ class UniPC: t = torch.linspace(t_T**(1. / t_order), t_0**(1. / t_order), N + 1).pow(t_order).to(device) return t else: - raise ValueError("Unsupported skip_type {}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'".format(skip_type)) + raise ValueError(f"Unsupported skip_type {skip_type}, need to be 'logSNR' or 'time_uniform' or 'time_quadratic'") def get_orders_and_timesteps_for_singlestep_solver(self, steps, order, skip_type, t_T, t_0, device): """ |