Merge pull request #1283 from jn-jairo/fix-vram (2cfcb23c) · Commits · github_fork / Stable Diffusion Webui

modules/extras.py

+2 −0

Original line number	Diff line number	Diff line
		@@ -100,6 +100,8 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v

		outputs.append(image)

		devices.torch_gc()

		return outputs, plaintext_to_html(info), ''

+15 −1

Original line number	Diff line number	Diff line
		@@ -11,7 +11,7 @@ import cv2
		from skimage import exposure

		import modules.sd_hijack
		from modules import devices, prompt_parser, masking, sd_samplers
		from modules import devices, prompt_parser, masking, sd_samplers, lowvram
		from modules.sd_hijack import model_hijack
		from modules.shared import opts, cmd_opts, state
		import modules.shared as shared
		@@ -382,6 +382,13 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
		x_samples_ddim = p.sd_model.decode_first_stage(samples_ddim)
		x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)

		del samples_ddim

		if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
		lowvram.send_everything_to_cpu()

		devices.torch_gc()

		if opts.filter_nsfw:
		import modules.safety as safety
		x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)
		@@ -426,6 +433,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
		infotexts.append(infotext(n, i))
		output_images.append(image)

		del x_samples_ddim

		devices.torch_gc()

		state.nextjob()

		p.color_corrections = None
		@@ -663,4 +674,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
		if self.mask is not None:
		samples = samples * self.nmask + self.init_latent * self.mask

		del x
		devices.torch_gc()

		return samples

+3 −1

Original line number	Diff line number	Diff line
		@@ -5,6 +5,7 @@ import traceback
		import torch
		import numpy as np
		from torch import einsum
		from torch.nn.functional import silu

		import modules.textual_inversion.textual_inversion
		from modules import prompt_parser, devices, sd_hijack_optimizations, shared
		@@ -19,11 +20,12 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At


		def apply_optimizations():
		ldm.modules.diffusionmodules.model.nonlinearity = silu

		if cmd_opts.opt_split_attention_v1:
		ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward_v1
		elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
		ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
		ldm.modules.diffusionmodules.model.nonlinearity = sd_hijack_optimizations.nonlinearity_hijack
		ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward

+0 −8

Original line number	Diff line number	Diff line
		@@ -92,14 +92,6 @@ def split_cross_attention_forward(self, x, context=None, mask=None):

		return self.to_out(r2)

		def nonlinearity_hijack(x):
		# swish
		t = torch.sigmoid(x)
		x *= t
		del t

		return x

		def cross_attention_attnblock_forward(self, x):
		h_ = x
		h_ = self.norm(h_)