multimodalart's picture
Squashing commit
4450790 verified
from nodes import LoraLoader
from .constants import get_category, get_name
from .power_prompt_utils import get_lora_by_filename
from .utils import FlexibleOptionalInputType, any_type
class RgthreePowerLoraLoader:
""" The Power Lora Loader is a powerful, flexible node to add multiple loras to a model/clip."""
NAME = get_name('Power Lora Loader')
CATEGORY = get_category()
@classmethod
def INPUT_TYPES(cls): # pylint: disable = invalid-name, missing-function-docstring
return {
"required": {
"model": ("MODEL",),
"clip": ("CLIP",),
},
# Since we will pass any number of loras in from the UI, this needs to always allow an
"optional": FlexibleOptionalInputType(any_type),
"hidden": {},
}
RETURN_TYPES = ("MODEL", "CLIP")
RETURN_NAMES = ("MODEL", "CLIP")
FUNCTION = "load_loras"
def load_loras(self, model, clip, **kwargs):
"""Loops over the provided loras in kwargs and applies valid ones."""
for key, value in kwargs.items():
key = key.upper()
if key.startswith('LORA_') and 'on' in value and 'lora' in value and 'strength' in value:
strength_model = value['strength']
# If we just passed one strtength value, then use it for both, if we passed a strengthTwo
# as well, then our `strength` will be for the model, and `strengthTwo` for clip.
strength_clip = value['strengthTwo'] if 'strengthTwo' in value and value[
'strengthTwo'] is not None else strength_model
if value['on'] and (strength_model != 0 or strength_clip != 0):
lora = get_lora_by_filename(value['lora'], log_node=self.NAME)
if lora is not None:
model, clip = LoraLoader().load_lora(model, clip, lora, strength_model, strength_clip)
return (model, clip)