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Refactored Loras

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This commit is contained in:
DeepBeepMeep
2025-03-14 23:43:04 +01:00
parent 48b777ae6c
commit d233dd7ed9
7 changed files with 344 additions and 115 deletions
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6
wan/text2video.py
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@@ -243,6 +243,10 @@ class WanT2V:
arg_null = {'context': context_null, 'seq_len': seq_len, 'freqs': freqs, 'pipeline': self}
arg_both = {'context': context, 'context2': context_null, 'seq_len': seq_len, 'freqs': freqs, 'pipeline': self}
# arg_c = {'context': context, 'seq_len': seq_len, 'freqs': freqs, 'pipeline': self, "max_steps": sampling_steps}
# arg_null = {'context': context_null, 'seq_len': seq_len, 'freqs': freqs, 'pipeline': self, "max_steps": sampling_steps}
# arg_both = {'context': context, 'context2': context_null, 'seq_len': seq_len, 'freqs': freqs, 'pipeline': self, "max_steps": sampling_steps}
if self.model.enable_teacache:
self.model.compute_teacache_threshold(self.model.teacache_start_step, timesteps, self.model.teacache_multiplier)
if callback != None:
@@ -250,7 +254,7 @@ class WanT2V:
for i, t in enumerate(tqdm(timesteps)):
latent_model_input = latents
timestep = [t]
offload.set_step_no_for_lora(i)
offload.set_step_no_for_lora(self.model, i)
timestep = torch.stack(timestep)
# self.model.to(self.device)