fix double gc and decoding with unet context (97431f29) · Commits · github_fork / Stable Diffusion Webui

modules/processing.py

+2 −3

Original line number	Original line	Diff line number	Diff line
	@@ -874,7 +874,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
	else:		else:
	if opts.sd_vae_decode_method != 'Full':		if opts.sd_vae_decode_method != 'Full':
	p.extra_generation_params['VAE Decoder'] = opts.sd_vae_decode_method		p.extra_generation_params['VAE Decoder'] = opts.sd_vae_decode_method
	with hypertile_context_unet(p.sd_model.model, aspect_ratio=p.width / p.height, tile_size=largest_tile_size_available(p.width, p.height), is_sdxl=shared.sd_model.is_sdxl, opts=shared.opts):		with hypertile_context_vae(p.sd_model.first_stage_model, aspect_ratio=p.width / p.height, tile_size=largest_tile_size_available(p.width, p.height), opts=shared.opts):
	x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True)		x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True)

	x_samples_ddim = torch.stack(x_samples_ddim).float()		x_samples_ddim = torch.stack(x_samples_ddim).float()
	@@ -1146,11 +1146,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
	tile_size = largest_tile_size_available(self.width, self.height)		tile_size = largest_tile_size_available(self.width, self.height)
	with hypertile_context_vae(self.sd_model.first_stage_model, aspect_ratio=aspect_ratio, tile_size=tile_size, opts=shared.opts):		with hypertile_context_vae(self.sd_model.first_stage_model, aspect_ratio=aspect_ratio, tile_size=tile_size, opts=shared.opts):
	with hypertile_context_unet(self.sd_model.model, aspect_ratio=aspect_ratio, tile_size=tile_size, is_sdxl=shared.sd_model.is_sdxl, opts=shared.opts):		with hypertile_context_unet(self.sd_model.model, aspect_ratio=aspect_ratio, tile_size=tile_size, is_sdxl=shared.sd_model.is_sdxl, opts=shared.opts):
	devices.torch_gc()
	samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))		samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
	del x		del x
	if not self.enable_hr:		if not self.enable_hr:
	return samples		return samples
			devices.torch_gc()

	if self.latent_scale_mode is None:		if self.latent_scale_mode is None:
	with hypertile_context_vae(self.sd_model.first_stage_model, aspect_ratio=aspect_ratio, tile_size=tile_size, opts=shared.opts):		with hypertile_context_vae(self.sd_model.first_stage_model, aspect_ratio=aspect_ratio, tile_size=tile_size, opts=shared.opts):
	@@ -1536,7 +1536,6 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
	tile_size = largest_tile_size_available(self.width, self.height)		tile_size = largest_tile_size_available(self.width, self.height)
	with hypertile_context_vae(self.sd_model.first_stage_model, aspect_ratio=aspect_ratio, tile_size=tile_size, opts=shared.opts):		with hypertile_context_vae(self.sd_model.first_stage_model, aspect_ratio=aspect_ratio, tile_size=tile_size, opts=shared.opts):
	with hypertile_context_unet(self.sd_model.model, aspect_ratio=aspect_ratio, tile_size=tile_size, is_sdxl=shared.sd_model.is_sdxl, opts=shared.opts):		with hypertile_context_unet(self.sd_model.model, aspect_ratio=aspect_ratio, tile_size=tile_size, is_sdxl=shared.sd_model.is_sdxl, opts=shared.opts):
	devices.torch_gc()
	samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)		samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)

	if self.mask is not None:		if self.mask is not None:

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