fix CLIP doing the unneeded normalization (594c8e7b) · Commits · github_fork / Stable Diffusion Webui

modules/processing.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -344,7 +344,7 @@ class StableDiffusionProcessing:

		def setup_conds(self):
		prompts = prompt_parser.SdConditioning(self.prompts, width=self.width, height=self.height)
		negative_prompts = prompt_parser.SdConditioning(self.negative_prompts, width=self.width, height=self.height)
		negative_prompts = prompt_parser.SdConditioning(self.negative_prompts, width=self.width, height=self.height, is_negative_prompt=True)

		sampler_config = sd_samplers.find_sampler_config(self.sampler_name)
		self.step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1

+10 −4

Original line number	Diff line number	Diff line
		@@ -116,11 +116,17 @@ class SdConditioning(list):
		A list with prompts for stable diffusion's conditioner model.
		Can also specify width and height of created image - SDXL needs it.
		"""
		def __init__(self, prompts, width=None, height=None):
		def __init__(self, prompts, is_negative_prompt=False, width=None, height=None, copy_from=None):
		super().__init__()
		self.extend(prompts)
		self.width = width or getattr(prompts, 'width', None)
		self.height = height or getattr(prompts, 'height', None)

		if copy_from is None:
		copy_from = prompts

		self.is_negative_prompt = is_negative_prompt or getattr(copy_from, 'is_negative_prompt', False)
		self.width = width or getattr(copy_from, 'width', None)
		self.height = height or getattr(copy_from, 'height', None)



		def get_learned_conditioning(model, prompts: SdConditioning \| list[str], steps):
		@@ -153,7 +159,7 @@ def get_learned_conditioning(model, prompts: SdConditioning \| list[str], steps):
		res.append(cached)
		continue

		texts = [x[1] for x in prompt_schedule]
		texts = SdConditioning([x[1] for x in prompt_schedule], copy_from=prompts)
		conds = model.get_learned_conditioning(texts)

		cond_schedule = []

+1 −1

Original line number	Diff line number	Diff line
		@@ -190,7 +190,7 @@ class StableDiffusionModelHijack:
		if typename == 'FrozenCLIPEmbedder':
		model_embeddings = m.cond_stage_model.transformer.text_model.embeddings
		model_embeddings.token_embedding = EmbeddingsWithFixes(model_embeddings.token_embedding, self)
		m.cond_stage_model = sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords(embedder, self)
		m.cond_stage_model = sd_hijack_clip.FrozenCLIPEmbedderForSDXLWithCustomWords(embedder, self)
		conditioner.embedders[i] = m.cond_stage_model
		if typename == 'FrozenOpenCLIPEmbedder2':
		embedder.model.token_embedding = EmbeddingsWithFixes(embedder.model.token_embedding, self)

+15 −0

Original line number	Diff line number	Diff line
		@@ -323,3 +323,18 @@ class FrozenCLIPEmbedderWithCustomWords(FrozenCLIPEmbedderWithCustomWordsBase):
		embedded = embedding_layer.token_embedding.wrapped(ids.to(embedding_layer.token_embedding.wrapped.weight.device)).squeeze(0)

		return embedded


		class FrozenCLIPEmbedderForSDXLWithCustomWords(FrozenCLIPEmbedderWithCustomWords):
		def __init__(self, wrapped, hijack):
		super().__init__(wrapped, hijack)

		def encode_with_transformers(self, tokens):
		outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=self.wrapped.layer == "hidden")

		if self.wrapped.layer == "last":
		z = outputs.last_hidden_state
		else:
		z = outputs.hidden_states[self.wrapped.layer_idx]

		return z

+0 −1

Original line number	Diff line number	Diff line
		@@ -12,7 +12,6 @@ sd_xl_repo_configs_path = os.path.join(paths.paths['Stable Diffusion XL'], "conf
		config_default = shared.sd_default_config
		config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml")
		config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml")
		config_sd2v = os.path.join(sd_xl_repo_configs_path, "sd_2_1_768.yaml")
		config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml")
		config_sdxl = os.path.join(sd_xl_repo_configs_path, "sd_xl_base.yaml")
		config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml")