Merge pull request #7730 from CCRcmcpe/fix-dpm-sde-batch (a77ac2ee) · Commits · github_fork / Stable Diffusion Webui

modules/sd_samplers_kdiffusion.py

+30 −8

Original line number	Diff line number	Diff line
		@@ -269,6 +269,16 @@ class KDiffusionSampler:

		return sigmas

		def create_noise_sampler(self, x, sigmas, p):
		"""For DPM++ SDE: manually create noise sampler to enable deterministic results across different batch sizes"""
		if shared.opts.no_dpmpp_sde_batch_determinism:
		return None

		from k_diffusion.sampling import BrownianTreeNoiseSampler
		sigma_min, sigma_max = sigmas[sigmas > 0].min(), sigmas.max()
		current_iter_seeds = p.all_seeds[p.iteration * p.batch_size:(p.iteration + 1) * p.batch_size]
		return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=current_iter_seeds)

		def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
		steps, t_enc = sd_samplers_common.setup_img2img_steps(p, steps)

		@@ -278,18 +288,24 @@ class KDiffusionSampler:
		xi = x + noise * sigma_sched[0]

		extra_params_kwargs = self.initialize(p)
		if 'sigma_min' in inspect.signature(self.func).parameters:
		parameters = inspect.signature(self.func).parameters

		if 'sigma_min' in parameters:
		## last sigma is zero which isn't allowed by DPM Fast & Adaptive so taking value before last
		extra_params_kwargs['sigma_min'] = sigma_sched[-2]
		if 'sigma_max' in inspect.signature(self.func).parameters:
		if 'sigma_max' in parameters:
		extra_params_kwargs['sigma_max'] = sigma_sched[0]
		if 'n' in inspect.signature(self.func).parameters:
		if 'n' in parameters:
		extra_params_kwargs['n'] = len(sigma_sched) - 1
		if 'sigma_sched' in inspect.signature(self.func).parameters:
		if 'sigma_sched' in parameters:
		extra_params_kwargs['sigma_sched'] = sigma_sched
		if 'sigmas' in inspect.signature(self.func).parameters:
		if 'sigmas' in parameters:
		extra_params_kwargs['sigmas'] = sigma_sched

		if self.funcname == 'sample_dpmpp_sde':
		noise_sampler = self.create_noise_sampler(x, sigmas, p)
		extra_params_kwargs['noise_sampler'] = noise_sampler

		self.model_wrap_cfg.init_latent = x
		self.last_latent = x
		extra_args={
		@@ -311,14 +327,20 @@ class KDiffusionSampler:
		x = x * sigmas[0]

		extra_params_kwargs = self.initialize(p)
		if 'sigma_min' in inspect.signature(self.func).parameters:
		parameters = inspect.signature(self.func).parameters

		if 'sigma_min' in parameters:
		extra_params_kwargs['sigma_min'] = self.model_wrap.sigmas[0].item()
		extra_params_kwargs['sigma_max'] = self.model_wrap.sigmas[-1].item()
		if 'n' in inspect.signature(self.func).parameters:
		if 'n' in parameters:
		extra_params_kwargs['n'] = steps
		else:
		extra_params_kwargs['sigmas'] = sigmas

		if self.funcname == 'sample_dpmpp_sde':
		noise_sampler = self.create_noise_sampler(x, sigmas, p)
		extra_params_kwargs['noise_sampler'] = noise_sampler

		self.last_latent = x
		samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
		'cond': conditioning,

modules/shared.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -414,6 +414,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
		options_templates.update(options_section(('compatibility', "Compatibility"), {
		"use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."),
		"use_old_karras_scheduler_sigmas": OptionInfo(False, "Use old karras scheduler sigmas (0.1 to 10)."),
		"no_dpmpp_sde_batch_determinism": OptionInfo(False, "Do not make DPM++ SDE deterministic across different batch sizes."),
		"use_old_hires_fix_width_height": OptionInfo(False, "For hires fix, use width/height sliders to set final resolution rather than first pass (disables Upscale by, Resize width/height to)."),
		}))

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