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RUIF013 updates and formatting

pull/4706/head
awsr 2026-03-24 05:12:18 -07:00
parent 4f0fb7cc29
commit 62d2229520
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3 changed files with 8 additions and 22 deletions
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2
modules/prompt_parser_diffusers.py
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@ -753,7 +753,7 @@ def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", c
return prompt_embeds, pooled_prompt_embeds, None, negative_prompt_embeds, negative_pooled_prompt_embeds, None return prompt_embeds, pooled_prompt_embeds, None, negative_prompt_embeds, negative_pooled_prompt_embeds, None
def get_xhinker_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int = None): def get_xhinker_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int | None = None):
is_sd3 = hasattr(pipe, 'text_encoder_3') is_sd3 = hasattr(pipe, 'text_encoder_3')
prompt, prompt_2, _prompt_3, _ = split_prompts(pipe, prompt, is_sd3) prompt, prompt_2, _prompt_3, _ = split_prompts(pipe, prompt, is_sd3)
neg_prompt, neg_prompt_2, _neg_prompt_3, _ = split_prompts(pipe, neg_prompt, is_sd3) neg_prompt, neg_prompt_2, _neg_prompt_3, _ = split_prompts(pipe, neg_prompt, is_sd3)

20
modules/prompt_parser_xhinker.py
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@ -27,10 +27,7 @@ from diffusers import ChromaPipeline
from modules.prompt_parser import parse_prompt_attention # use built-in A1111 parser from modules.prompt_parser import parse_prompt_attention # use built-in A1111 parser
def get_prompts_tokens_with_weights( def get_prompts_tokens_with_weights(clip_tokenizer: CLIPTokenizer, prompt: str | None = None):
clip_tokenizer: CLIPTokenizer
, prompt: str = None
):
""" """
Get prompt token ids and weights, this function works for both prompt and negative prompt Get prompt token ids and weights, this function works for both prompt and negative prompt
@ -754,13 +751,7 @@ def get_weighted_text_embeddings_sdxl_refiner(
return prompt_embeds, negative_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds return prompt_embeds, negative_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
def get_weighted_text_embeddings_sdxl_2p( def get_weighted_text_embeddings_sdxl_2p(pipe: StableDiffusionXLPipeline, prompt: str = "", prompt_2: str | None = None, neg_prompt: str = "", neg_prompt_2: str | None = None):
pipe: StableDiffusionXLPipeline
, prompt: str = ""
, prompt_2: str = None
, neg_prompt: str = ""
, neg_prompt_2: str = None
):
""" """
This function can process long prompt with weights, no length limitation This function can process long prompt with weights, no length limitation
for Stable Diffusion XL, support two prompt sets. for Stable Diffusion XL, support two prompt sets.
@ -1345,12 +1336,7 @@ def get_weighted_text_embeddings_sd3(
return sd3_prompt_embeds, sd3_neg_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds return sd3_prompt_embeds, sd3_neg_prompt_embeds, pooled_prompt_embeds, negative_pooled_prompt_embeds
def get_weighted_text_embeddings_flux1( def get_weighted_text_embeddings_flux1(pipe: FluxPipeline, prompt: str = "", prompt2: str | None = None, device=None):
pipe: FluxPipeline
, prompt: str = ""
, prompt2: str = None
, device=None
):
""" """
This function can process long prompt with weights for flux1 model This function can process long prompt with weights for flux1 model

8
modules/ras/ras_forward.py
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@ -22,10 +22,10 @@ from . import ras_manager
def ras_forward( def ras_forward(
self, self,
hidden_states: torch.FloatTensor, hidden_states: torch.FloatTensor,
encoder_hidden_states: torch.FloatTensor = None, encoder_hidden_states: torch.FloatTensor | None = None,
pooled_projections: torch.FloatTensor = None, pooled_projections: torch.FloatTensor | None = None,
timestep: torch.LongTensor = None, timestep: torch.LongTensor | None = None,
block_controlnet_hidden_states: list = None, block_controlnet_hidden_states: list | None = None,
joint_attention_kwargs: dict[str, Any] | None = None, joint_attention_kwargs: dict[str, Any] | None = None,
return_dict: bool = True, return_dict: bool = True,
skip_layers: list[int] | None = None, skip_layers: list[int] | None = None,