Merge branch 'master' into dev/deepdanbooru (0ec80f01) · Commits · github_fork / Stable Diffusion Webui

launch.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -127,7 +127,7 @@ if not is_installed("gfpgan"):
		if not is_installed("clip"):
		run_pip(f"install {clip_package}", "clip")

		if not is_installed("xformers") and xformers:
		if not is_installed("xformers") and xformers and platform.python_version().startswith("3.10"):
		if platform.system() == "Windows":
		run_pip("install https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/a/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl", "xformers")
		elif platform.system() == "Linux":

+7 −2

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		@@ -13,13 +13,14 @@ import lark

		schedule_parser = lark.Lark(r"""
		!start: (prompt \| /[][():]/+)*
		prompt: (emphasized \| scheduled \| plain \| WHITESPACE)*
		prompt: (emphasized \| scheduled \| alternate \| plain \| WHITESPACE)*
		!emphasized: "(" prompt ")"
		\| "(" prompt ":" prompt ")"
		\| "[" prompt "]"
		scheduled: "[" [prompt ":"] prompt ":" [WHITESPACE] NUMBER "]"
		alternate: "[" prompt ("\|" prompt)+ "]"
		WHITESPACE: /\s+/
		plain: /([^\\\[\]():]\|\\.)+/
		plain: /([^\\\[\]():\|]\|\\.)+/
		%import common.SIGNED_NUMBER -> NUMBER
		""")

		@@ -59,6 +60,8 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
		tree.children[-1] *= steps
		tree.children[-1] = min(steps, int(tree.children[-1]))
		l.append(tree.children[-1])
		def alternate(self, tree):
		l.extend(range(1, steps+1))
		CollectSteps().visit(tree)
		return sorted(set(l))

		@@ -67,6 +70,8 @@ def get_learned_conditioning_prompt_schedules(prompts, steps):
		def scheduled(self, args):
		before, after, _, when = args
		yield before or () if step <= when else after
		def alternate(self, args):
		yield next(args[(step - 1)%len(args)])
		def start(self, args):
		def flatten(x):
		if type(x) == str:

+5 −1

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		@@ -22,12 +22,16 @@ def apply_optimizations():
		undo_optimizations()

		ldm.modules.diffusionmodules.model.nonlinearity = silu
		if cmd_opts.xformers and shared.xformers_available and not torch.version.hip:

		if cmd_opts.force_enable_xformers or (cmd_opts.xformers and shared.xformers_available and torch.version.cuda and torch.cuda.get_device_capability(shared.device) == (8, 6)):
		print("Applying xformers cross attention optimization.")
		ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward
		ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward
		elif cmd_opts.opt_split_attention_v1:
		print("Applying v1 cross attention optimization.")
		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()):
		print("Applying cross attention optimization.")
		ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.split_cross_attention_forward
		ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.cross_attention_attnblock_forward

+4 −1

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		@@ -211,6 +211,7 @@ def cross_attention_attnblock_forward(self, x):
		return h3

		def xformers_attnblock_forward(self, x):
		try:
		h_ = x
		h_ = self.norm(h_)
		q1 = self.q(h_).contiguous()
		@@ -219,3 +220,5 @@ def xformers_attnblock_forward(self, x):
		out = xformers.ops.memory_efficient_attention(q1, k1, v)
		out = self.proj_out(out)
		return x + out
		except NotImplementedError:
		return cross_attention_attnblock_forward(self, x)

+1 −0

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		@@ -44,6 +44,7 @@ parser.add_argument("--scunet-models-path", type=str, help="Path to directory wi
		parser.add_argument("--swinir-models-path", type=str, help="Path to directory with SwinIR model file(s).", default=os.path.join(models_path, 'SwinIR'))
		parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(models_path, 'LDSR'))
		parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
		parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")
		parser.add_argument("--deepdanbooru", action='store_true', help="enable deepdanbooru interrogator")
		parser.add_argument("--opt-split-attention", action='store_true', help="force-enables cross-attention layer optimization. By default, it's on for torch.cuda and off for other torch devices.")
		parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")