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Simplify differential diffusion code.

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comfyanonymous
2024-03-03 15:11:13 -05:00
parent 727021bdea
commit 12c1080ebc
3 changed files with 23 additions and 74 deletions
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7
comfy/samplers.py
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@@ -272,13 +272,14 @@ class CFGNoisePredictor(torch.nn.Module):
return self.apply_model(*args, **kwargs)
class KSamplerX0Inpaint(torch.nn.Module):
def __init__(self, model):
def __init__(self, model, sigmas):
super().__init__()
self.inner_model = model
self.sigmas = sigmas
def forward(self, x, sigma, uncond, cond, cond_scale, denoise_mask, model_options={}, seed=None):
if denoise_mask is not None:
if "denoise_mask_function" in model_options:
denoise_mask = model_options["denoise_mask_function"](sigma, denoise_mask)
denoise_mask = model_options["denoise_mask_function"](sigma, denoise_mask, extra_options={"model": self.inner_model, "sigmas": self.sigmas})
latent_mask = 1. - denoise_mask
x = x * denoise_mask + self.inner_model.inner_model.model_sampling.noise_scaling(sigma.reshape([sigma.shape[0]] + [1] * (len(self.noise.shape) - 1)), self.noise, self.latent_image) * latent_mask
out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, model_options=model_options, seed=seed)
@@ -528,7 +529,7 @@ class KSAMPLER(Sampler):
def sample(self, model_wrap, sigmas, extra_args, callback, noise, latent_image=None, denoise_mask=None, disable_pbar=False):
extra_args["denoise_mask"] = denoise_mask
model_k = KSamplerX0Inpaint(model_wrap)
model_k = KSamplerX0Inpaint(model_wrap, sigmas)
model_k.latent_image = latent_image
if self.inpaint_options.get("random", False): #TODO: Should this be the default?
generator = torch.manual_seed(extra_args.get("seed", 41) + 1)