ImageCritic_ComfyUI / convert.py
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import argparse
import os
import sys
from safetensors.torch import load_file, save_file
class C:
HEADER = '\033[95m'
BLUE = '\033[94m'
CYAN = '\033[96m'
GREEN = '\033[92m'
YELLOW = '\033[93m'
RED = '\033[91m'
GREY = '\033[90m'
RESET = '\033[0m'
BOLD = '\033[1m'
def convert_key(old_key):
parts = old_key.split('.')
if "attn" not in parts or "processor" not in parts or "weight" not in parts:
return None
lora_type_idx = -1
for i, part in enumerate(parts):
if part.endswith('_loras'):
lora_type_idx = i
break
if lora_type_idx == -1:
return None
raw_type = parts[lora_type_idx].replace('_loras', '')
try:
direction = parts[lora_type_idx + 2]
except IndexError:
return None
type_map = {
"q": "to_q",
"k": "to_k",
"v": "to_v",
"proj": "to_out.0"
}
lora_map = {
"down": "lora_A",
"up": "lora_B"
}
if raw_type not in type_map or direction not in lora_map:
return None
new_type_str = type_map[raw_type]
new_lora_str = lora_map[direction]
prefix_parts = parts[:lora_type_idx - 1]
prefix_str = ".".join(prefix_parts)
new_key = f"transformer.{prefix_str}.{new_type_str}.{new_lora_str}.weight"
return new_key
def main():
parser = argparse.ArgumentParser(description="Colorful LoRA Key Converter")
parser.add_argument("input_file", type=str, help="Input safetensors file")
parser.add_argument("output_file", type=str, help="Output safetensors file")
args = parser.parse_args()
if not os.path.exists(args.input_file):
print(f"{C.RED}Error: Input file '{args.input_file}' not found.{C.RESET}")
return
print(f"{C.HEADER}Loading weights from: {C.RESET}{C.BOLD}{args.input_file}{C.RESET}")
try:
tensors = load_file(args.input_file)
except Exception as e:
print(f"{C.RED}Failed to load file: {e}{C.RESET}")
return
new_tensors = {}
skipped_keys = []
print(f"{C.HEADER}{'-'*60}{C.RESET}")
print(f"{C.BOLD}Processing Keys:{C.RESET}")
for key, tensor in tensors.items():
new_key = convert_key(key)
if new_key:
print(f"{C.RED}{key}{C.RESET}")
print(f" ↓ {C.GREY}converted to{C.RESET}")
print(f"{C.GREEN}{new_key}{C.RESET}")
print(f"{C.GREY}-{C.RESET}" * 20)
new_tensors[new_key] = tensor
else:
skipped_keys.append(key)
print(f"\n{C.HEADER}Saving...{C.RESET}")
save_file(new_tensors, args.output_file)
print(f"{C.BOLD}Saved converted model to:{C.RESET} {C.CYAN}{args.output_file}{C.RESET}")
print(f"\n{C.HEADER}{'-'*60}{C.RESET}")
print(f"{C.YELLOW}Skipped Keys (Not Converted): {len(skipped_keys)}{C.RESET}")
if skipped_keys:
for sk in skipped_keys:
print(f" {C.GREY}{sk}{C.RESET}")
else:
print(f" {C.GREEN}(None - All keys were converted){C.RESET}")
print(f"{C.HEADER}{'-'*60}{C.RESET}")
print(f"Total Original Keys: {len(tensors)}")
print(f"Converted Keys: {C.GREEN}{len(new_tensors)}{C.RESET}")
print(f"Skipped Keys: {C.YELLOW}{len(skipped_keys)}{C.RESET}")
if __name__ == "__main__":
main()