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refactor: only use LoRA activate on handover to async worker, extract method

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This commit is contained in:
Manuel Schmid
2024-03-11 23:49:45 +01:00
parent 532401df76
commit 57a01865b9
5 changed files with 15 additions and 17 deletions
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modules/async_worker.py
+3 -11
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@@ -46,8 +46,8 @@ def worker():
from modules.sdxl_styles import apply_style, apply_wildcards, fooocus_expansion, apply_arrays
from modules.private_logger import log
from extras.expansion import safe_str
from modules.util import remove_empty_str, HWC3, resize_image, \
get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate, ordinal_suffix
from modules.util import remove_empty_str, HWC3, resize_image, get_image_shape_ceil, set_image_shape_ceil, \
get_shape_ceil, resample_image, erode_or_dilate, ordinal_suffix, get_enabled_loras
from modules.upscaler import perform_upscale
from modules.flags import Performance
from modules.meta_parser import get_metadata_parser, MetadataScheme
@@ -124,14 +124,6 @@ def worker():
async_task.results = async_task.results + [wall]
return
def apply_enabled_loras(loras):
enabled_loras = []
for lora_enabled, lora_model, lora_weight in loras:
if lora_enabled:
enabled_loras.append([lora_model, lora_weight])
return enabled_loras
@torch.no_grad()
@torch.inference_mode()
def handler(async_task):
@@ -155,7 +147,7 @@ def worker():
base_model_name = args.pop()
refiner_model_name = args.pop()
refiner_switch = args.pop()
loras = apply_enabled_loras([[bool(args.pop()), str(args.pop()), float(args.pop()), ] for _ in range(modules.config.default_max_lora_number)])
loras = get_enabled_loras([[bool(args.pop()), str(args.pop()), float(args.pop())] for _ in range(modules.config.default_max_lora_number)])
input_image_checkbox = args.pop()
current_tab = args.pop()
uov_method = args.pop()