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feat: inline lora optimisations (#2967)

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* feat: add performance loras to the end of the loras array

* fix: resolve circular dependency for unit tests

* feat: allow multiple matches for each token, optimize and extract method cleanup_prompt

* fix: update unit tests

* feat: ignore custom wildcards
This commit is contained in:
Manuel Schmid
2024-05-20 17:31:51 +02:00
committed by GitHub
parent c995511705
commit 65a8b25129
6 changed files with 93 additions and 37 deletions
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modules/async_worker.py
+7 -5
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@@ -237,10 +237,12 @@ def worker():
steps = performance_selection.steps()
performance_loras = []
if performance_selection == Performance.EXTREME_SPEED:
print('Enter LCM mode.')
progressbar(async_task, 1, 'Downloading LCM components ...')
loras += [(modules.config.downloading_sdxl_lcm_lora(), 1.0)]
performance_loras += [(modules.config.downloading_sdxl_lcm_lora(), 1.0)]
if refiner_model_name != 'None':
print(f'Refiner disabled in LCM mode.')
@@ -259,7 +261,7 @@ def worker():
elif performance_selection == Performance.LIGHTNING:
print('Enter Lightning mode.')
progressbar(async_task, 1, 'Downloading Lightning components ...')
loras += [(modules.config.downloading_sdxl_lightning_lora(), 1.0)]
performance_loras += [(modules.config.downloading_sdxl_lightning_lora(), 1.0)]
if refiner_model_name != 'None':
print(f'Refiner disabled in Lightning mode.')
@@ -278,7 +280,7 @@ def worker():
elif performance_selection == Performance.HYPER_SD:
print('Enter Hyper-SD mode.')
progressbar(async_task, 1, 'Downloading Hyper-SD components ...')
loras += [(modules.config.downloading_sdxl_hyper_sd_lora(), 0.8)]
performance_loras += [(modules.config.downloading_sdxl_hyper_sd_lora(), 0.8)]
if refiner_model_name != 'None':
print(f'Refiner disabled in Hyper-SD mode.')
@@ -458,8 +460,8 @@ def worker():
progressbar(async_task, 2, 'Loading models ...')
loras = parse_lora_references_from_prompt(prompt, loras, modules.config.default_max_lora_number)
loras, prompt = parse_lora_references_from_prompt(prompt, loras, modules.config.default_max_lora_number)
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)