Mirror/stable-diffusion-webui
1
0
Fork 0
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git synced 2024-06-07 21:20:49 +00:00
Code Issues Packages Projects Releases Wiki Activity

ignore errors in parse for purposes of token counting for #1564

Browse Source
This commit is contained in:
AUTOMATIC 2022-10-04 14:35:12 +03:00
parent b7f3996982
commit d5bba20a58
1 changed files with 10 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
modules/ui.py
View File

@ -386,14 +386,22 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
outputs=[seed, dummy_component] outputs=[seed, dummy_component]
) )
def update_token_counter(text, steps): def update_token_counter(text, steps):
prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps) try:
prompt_schedules = get_learned_conditioning_prompt_schedules([text], steps)
except Exception:
# a parsing error can happen here during typing, and we don't want to bother the user with
# messages related to it in console
prompt_schedules = [[[steps, text]]]
flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules) flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
prompts = [prompt_text for step,prompt_text in flat_prompts] prompts = [prompt_text for step, prompt_text in flat_prompts]
tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1]) tokens, token_count, max_length = max([model_hijack.tokenize(prompt) for prompt in prompts], key=lambda args: args[1])
style_class = ' class="red"' if (token_count > max_length) else "" style_class = ' class="red"' if (token_count > max_length) else ""
return f"<span {style_class}>{token_count}/{max_length}</span>" return f"<span {style_class}>{token_count}/{max_length}</span>"
def create_toprow(is_img2img): def create_toprow(is_img2img):
id_part = "img2img" if is_img2img else "txt2img" id_part = "img2img" if is_img2img else "txt2img"