theluyuan/DiffSynth-Studio
1
0
Fork 0
mirror of https://github.com/modelscope/DiffSynth-Studio.git synced 2026-03-23 00:58:11 +00:00
Code Issues Packages Projects Releases Wiki Activity

fix wan i2v train bug

Browse Source
This commit is contained in:
Kared
2026-01-27 03:55:36 +00:00
parent ffb7a138f7
commit 8d0df403ca
1 changed files with 7 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
diffsynth/diffusion/loss.py
View File

@@ -13,9 +13,16 @@ def FlowMatchSFTLoss(pipe: BasePipeline, **inputs):
inputs["latents"] = pipe.scheduler.add_noise(inputs["input_latents"], noise, timestep) inputs["latents"] = pipe.scheduler.add_noise(inputs["input_latents"], noise, timestep)
training_target = pipe.scheduler.training_target(inputs["input_latents"], noise, timestep) training_target = pipe.scheduler.training_target(inputs["input_latents"], noise, timestep)
if "first_frame_latents" in inputs:
inputs["latents"][:, :, 0:1] = inputs["first_frame_latents"]
models = {name: getattr(pipe, name) for name in pipe.in_iteration_models} models = {name: getattr(pipe, name) for name in pipe.in_iteration_models}
noise_pred = pipe.model_fn(**models, **inputs, timestep=timestep) noise_pred = pipe.model_fn(**models, **inputs, timestep=timestep)
if "first_frame_latents" in inputs:
noise_pred = noise_pred[:, :, 1:]
training_target = training_target[:, :, 1:]
loss = torch.nn.functional.mse_loss(noise_pred.float(), training_target.float()) loss = torch.nn.functional.mse_loss(noise_pred.float(), training_target.float())
loss = loss * pipe.scheduler.training_weight(timestep) loss = loss * pipe.scheduler.training_weight(timestep)
return loss return loss