
'''simple docstring'''







import argparse

import torch
from safetensors.torch import load_file

from diffusers import StableDiffusionPipeline
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			Optional[int]				,				__SCREAMING_SNAKE_CASE :			int				,				__SCREAMING_SNAKE_CASE :			List[str]				,				__SCREAMING_SNAKE_CASE :			int				,				__SCREAMING_SNAKE_CASE :			List[str]							):



						"""simple docstring"""





						lowercase_     :					List[str]													=	StableDiffusionPipeline.from_pretrained(__SCREAMING_SNAKE_CASE				,				torch_dtype=torch.floataa							)

						# load LoRA weight from .safetensors
						lowercase_     :					Optional[int]													=	load_file(__SCREAMING_SNAKE_CASE							)

						lowercase_     :					Any													=	[]

						# directly update weight in diffusers model
						for key in state_dict:
												# it is suggested to print out the key, it usually will be something like below
												# "lora_te_text_model_encoder_layers_0_self_attn_k_proj.lora_down.weight"

												# as we have set the alpha beforehand, so just skip
												if ".alpha" in key or key in visited:
																		continue

												if "text" in key:
																		lowercase_     :					Union[str, Any]													=	key.split('''.'''							)[0].split(LORA_PREFIX_TEXT_ENCODER + '''_'''							)[-1].split('''_'''							)
																		lowercase_     :					Optional[int]													=	pipeline.text_encoder
												else:
																		lowercase_     :					Optional[Any]													=	key.split('''.'''							)[0].split(LORA_PREFIX_UNET + '''_'''							)[-1].split('''_'''							)
																		lowercase_     :					str													=	pipeline.unet

												# find the target layer
												lowercase_     :					Union[str, Any]													=	layer_infos.pop(0							)
												while len(__SCREAMING_SNAKE_CASE							) > -1:
																		try:
																								lowercase_     :					str													=	curr_layer.__getattr__(__SCREAMING_SNAKE_CASE							)
																								if len(__SCREAMING_SNAKE_CASE							) > 0:
																														lowercase_     :					Dict													=	layer_infos.pop(0							)
																								elif len(__SCREAMING_SNAKE_CASE							) == 0:
																														break
																		except Exception:
																								if len(__SCREAMING_SNAKE_CASE							) > 0:
																														temp_name += "_" + layer_infos.pop(0							)
																								else:
																														lowercase_     :					int													=	layer_infos.pop(0							)

												lowercase_     :					Dict													=	[]
												if "lora_down" in key:
																		pair_keys.append(key.replace('''lora_down'''				,				'''lora_up'''							)							)
																		pair_keys.append(__SCREAMING_SNAKE_CASE							)
												else:
																		pair_keys.append(__SCREAMING_SNAKE_CASE							)
																		pair_keys.append(key.replace('''lora_up'''				,				'''lora_down'''							)							)

												# update weight
												if len(state_dict[pair_keys[0]].shape							) == 4:
																		lowercase_     :					List[str]													=	state_dict[pair_keys[0]].squeeze(3							).squeeze(2							).to(torch.floataa							)
																		lowercase_     :					List[Any]													=	state_dict[pair_keys[1]].squeeze(3							).squeeze(2							).to(torch.floataa							)
																		curr_layer.weight.data += alpha * torch.mm(__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE							).unsqueeze(2							).unsqueeze(3							)
												else:
																		lowercase_     :					Any													=	state_dict[pair_keys[0]].to(torch.floataa							)
																		lowercase_     :					List[Any]													=	state_dict[pair_keys[1]].to(torch.floataa							)
																		curr_layer.weight.data += alpha * torch.mm(__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE							)

												# update visited list
												for item in pair_keys:
																		visited.append(__SCREAMING_SNAKE_CASE							)

						return pipeline


if __name__ == "__main__":
							_lowercase			:  Optional[int]   							=	argparse.ArgumentParser()

							parser.add_argument(
							    "--base_model_path", default=None, type=str, required=True, help="Path to the base model in diffusers format."
							)
							parser.add_argument(
							    "--checkpoint_path", default=None, type=str, required=True, help="Path to the checkpoint to convert."
							)
							parser.add_argument("--dump_path", default=None, type=str, required=True, help="Path to the output model.")
							parser.add_argument(
							    "--lora_prefix_unet", default="lora_unet", type=str, help="The prefix of UNet weight in safetensors"
							)
							parser.add_argument(
							    "--lora_prefix_text_encoder",
							    default="lora_te",
							    type=str,
							    help="The prefix of text encoder weight in safetensors",
							)
							parser.add_argument("--alpha", default=0.7_5, type=float, help="The merging ratio in W = W0 + alpha * deltaW")
							parser.add_argument(
							    "--to_safetensors", action="store_true", help="Whether to store pipeline in safetensors format or not."
							)
							parser.add_argument("--device", type=str, help="Device to use (e.g. cpu, cuda:0, cuda:1, etc.)")

							_lowercase			:  str   							=	parser.parse_args()

							_lowercase			:  List[str]   							=	args.base_model_path
							_lowercase			:  Any   							=	args.checkpoint_path
							_lowercase			:  Dict   							=	args.dump_path
							_lowercase			:  Tuple   							=	args.lora_prefix_unet
							_lowercase			:  Tuple   							=	args.lora_prefix_text_encoder
							_lowercase			:  Optional[Any]   							=	args.alpha

							_lowercase			:  List[str]   							=	convert(base_model_path, checkpoint_path, lora_prefix_unet, lora_prefix_text_encoder, alpha)

							_lowercase			:  List[Any]   							=	pipe.to(args.device)
							pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)





'''simple docstring'''







from __future__ import annotations






class 			lowerCAmelCase__       :






					def __init__(       self    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											lowercase_     :					Any													=	key






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					List[str]													=	key or self.__key or 1

											# make sure key is an appropriate size
											key %= 2_55

											return [chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		) for ch in content]






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Optional[int]													=	key or self.__key or 1

											# make sure key is an appropriate size
											key %= 2_55

											return [chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		) for ch in content]






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					List[Any]													=	key or self.__key or 1

											# make sure key can be any size
											while key > 2_55:
																	key -= 2_55

											# This will be returned
											lowercase_     :					str													=	''''''

											for ch in content:
																	ans += chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		)

											return ans






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											lowercase_     :					Any													=	key or self.__key or 1

											# make sure key can be any size
											while key > 2_55:
																	key -= 2_55

											# This will be returned
											lowercase_     :					Dict													=	''''''

											for ch in content:
																	ans += chr(ord(__SCREAMING_SNAKE_CASE		) ^ key		)

											return ans






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = 0		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											try:
																	with open(__SCREAMING_SNAKE_CASE		) as fin, open('''encrypt.out'''    ,							'''w+'''		) as fout:
																							# actual encrypt-process
																							for line in fin:
																													fout.write(self.encrypt_string(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)		)

											except OSError:
																	return False

											return True






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											assert isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		) and isinstance(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)

											try:
																	with open(__SCREAMING_SNAKE_CASE		) as fin, open('''decrypt.out'''    ,							'''w+'''		) as fout:
																							# actual encrypt-process
																							for line in fin:
																													fout.write(self.decrypt_string(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE		)		)

											except OSError:
																	return False

											return True


# Tests
# crypt = XORCipher()
# key = 67

# # test encrypt
# print(crypt.encrypt("hallo welt",key))
# # test decrypt
# print(crypt.decrypt(crypt.encrypt("hallo welt",key), key))

# # test encrypt_string
# print(crypt.encrypt_string("hallo welt",key))

# # test decrypt_string
# print(crypt.decrypt_string(crypt.encrypt_string("hallo welt",key),key))

# if (crypt.encrypt_file("test.txt",key)):
#       print("encrypt successful")
# else:
#       print("encrypt unsuccessful")

# if (crypt.decrypt_file("encrypt.out",key)):
#       print("decrypt successful")
# else:
#       print("decrypt unsuccessful")



