separate part of denoiser code into a function to make it easier for extensions to override it (0b8acce6) · Commits · github_fork / Stable Diffusion Webui

modules/sd_samplers.py

+11 −6

Original line number	Original line	Diff line number	Diff line
	@@ -288,6 +288,16 @@ class CFGDenoiser(torch.nn.Module):
	self.init_latent = None		self.init_latent = None
	self.step = 0		self.step = 0

			def combine_denoised(self, x_out, conds_list, uncond, cond_scale):
			denoised_uncond = x_out[-uncond.shape[0]:]
			denoised = torch.clone(denoised_uncond)

			for i, conds in enumerate(conds_list):
			for cond_index, weight in conds:
			denoised[i] += (x_out[cond_index] - denoised_uncond[i]) * (weight * cond_scale)

			return denoised

	def forward(self, x, sigma, uncond, cond, cond_scale, image_cond):		def forward(self, x, sigma, uncond, cond, cond_scale, image_cond):
	if state.interrupted or state.skipped:		if state.interrupted or state.skipped:
	raise InterruptedException		raise InterruptedException
	@@ -329,12 +339,7 @@ class CFGDenoiser(torch.nn.Module):

	x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond={"c_crossattn": [uncond], "c_concat": [image_cond_in[-uncond.shape[0]:]]})		x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond={"c_crossattn": [uncond], "c_concat": [image_cond_in[-uncond.shape[0]:]]})

	denoised_uncond = x_out[-uncond.shape[0]:]		denoised = self.combine_denoised(x_out, conds_list, uncond, cond_scale)
	denoised = torch.clone(denoised_uncond)

	for i, conds in enumerate(conds_list):
	for cond_index, weight in conds:
	denoised[i] += (x_out[cond_index] - denoised_uncond[i]) * (weight * cond_scale)

	if self.mask is not None:		if self.mask is not None:
	denoised = self.init_latent * self.mask + self.nmask * denoised		denoised = self.init_latent * self.mask + self.nmask * denoised

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