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feat: optimize performance lora filtering in metadata (#3048)

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* feat: add remove_performance_lora method

* feat: use class PerformanceLoRA instead of strings in config

* refactor: cleanup flags, use __member__ to check if enums contains key

* feat: only filter lora of selected performance instead of all performance LoRAs

* fix: disable intermediate results for all restricted performances

too fast for Gradio, which becomes a bottleneck

* refactor: rename parse_json to to_json, rename parse_string to to_string

* feat: use speed steps as default instead of hardcoded 30

* feat: add method to_steps to Performance

* refactor: remove method ordinal_suffix, not needed anymore

* feat: only filter lora of selected performance instead of all performance LoRAs

both metadata and history log

* feat: do not filter LoRAs in metadata parser but rather in metadata load action
This commit is contained in:
Manuel Schmid
2024-05-30 16:14:28 +02:00
committed by GitHub
parent 3ef663c5b7
commit 4e658bb63a
8 changed files with 144 additions and 53 deletions
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modules/async_worker.py
+3 -1
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@@ -462,8 +462,10 @@ def worker():
progressbar(async_task, 2, 'Loading models ...')
loras, prompt = parse_lora_references_from_prompt(prompt, loras, modules.config.default_max_lora_number)
lora_filenames = modules.util.remove_performance_lora(modules.config.lora_filenames, performance_selection)
loras, prompt = parse_lora_references_from_prompt(prompt, loras, modules.config.default_max_lora_number, lora_filenames=lora_filenames)
loras += performance_loras
pipeline.refresh_everything(refiner_model_name=refiner_model_name, base_model_name=base_model_name,
loras=loras, base_model_additional_loras=base_model_additional_loras,
use_synthetic_refiner=use_synthetic_refiner, vae_name=vae_name)