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flip the vector direction to original again this time

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lodestone-rock 2026-02-28 21:36:28 +07:00
parent 033a534f7c
commit d1e7cafa6b
1 changed files with 9 additions and 7 deletions
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16
comfy/ldm/lumina/model.py
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@ -1164,18 +1164,20 @@ class NextDiTPixelSpace(NextDiT):
return -img_out
def forward(self, x, timesteps, context, num_tokens, attention_mask=None, **kwargs):
# _forward returns -x0 (negated decoder output, same convention as NextDiT).
# _forward returns neg_x0 = -x0 (negated decoder output).
#
# ComfyUI uses CONST sampling: calculate_denoised = x - model_output * sigma
# We need calculate_denoised to return x0, so model_output must equal (x - x0) / sigma.
# Reference inference (working_inference_reference.py):
# out = _forward(img, t) # = -x0
# pred = (img - out) / t # = (img + x0) / t [_apply_x0_residual]
# img += (t_prev - t_curr) * pred # Euler step
#
# _forward returns neg_x0 = -x0, so:
# model_output = (x + neg_x0) / sigma → (x + (-x0)) / sigma = (x - x0) / sigma ✓
# Then: x - model_output * sigma = x - (x - x0) = x0 ✓
# ComfyUI's Euler sampler does the same:
# x_next = x + (sigma_next - sigma) * model_output
# So model_output must equal pred = (x - neg_x0) / t = (x - (-x0)) / t = (x + x0) / t
neg_x0 = comfy.patcher_extension.WrapperExecutor.new_class_executor(
self._forward,
self,
comfy.patcher_extension.get_all_wrappers(comfy.patcher_extension.WrappersMP.DIFFUSION_MODEL, kwargs.get("transformer_options", {}))
).execute(x, timesteps, context, num_tokens, attention_mask, **kwargs)
return (x + neg_x0) / timesteps.view(-1, 1, 1, 1)
return (x - neg_x0) / timesteps.view(-1, 1, 1, 1)