




"""simple docstring"""







import argparse

import torch
from safetensors.torch import load_file

from diffusers import StableDiffusionPipeline

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase,  _lowerCamelCase				)			->str:
		__lowercase				:		Dict												=				StableDiffusionPipeline.from_pretrained(_lowerCamelCase,  torch_dtype=torch.floataa				)

		# load LoRA weight from .safetensors
		__lowercase				:		str												=				load_file(_lowerCamelCase				)

		__lowercase				:		Optional[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				:		List[Any]												=				key.split("."				)[0].split(LORA_PREFIX_TEXT_ENCODER + "_"				)[-1].split("_"				)
						__lowercase				:		Optional[Any]												=				pipeline.text_encoder
				else:
						__lowercase				:		Optional[Any]												=				key.split("."				)[0].split(LORA_PREFIX_UNET + "_"				)[-1].split("_"				)
						__lowercase				:		List[str]												=				pipeline.unet

				# find the target layer
				__lowercase				:		Dict												=				layer_infos.pop(0				)
				while len(_lowerCamelCase				) > -1:
						try:
								__lowercase				:		Dict												=				curr_layer.__getattr__(_lowerCamelCase				)
								if len(_lowerCamelCase				) > 0:
										__lowercase				:		int												=				layer_infos.pop(0				)
								elif len(_lowerCamelCase				) == 0:
										break
						except Exception:
								if len(_lowerCamelCase				) > 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(_lowerCamelCase				)
				else:
						pair_keys.append(_lowerCamelCase				)
						pair_keys.append(key.replace("lora_up",  "lora_down"				)				)

				# update weight
				if len(state_dict[pair_keys[0]].shape				) == 4:
						__lowercase				:		Optional[int]												=				state_dict[pair_keys[0]].squeeze(3				).squeeze(2				).to(torch.floataa				)
						__lowercase				:		Tuple												=				state_dict[pair_keys[1]].squeeze(3				).squeeze(2				).to(torch.floataa				)
						curr_layer.weight.data += alpha * torch.mm(_lowerCamelCase,  _lowerCamelCase				).unsqueeze(2				).unsqueeze(3				)
				else:
						__lowercase				:		Optional[Any]												=				state_dict[pair_keys[0]].to(torch.floataa				)
						__lowercase				:		Any												=				state_dict[pair_keys[1]].to(torch.floataa				)
						curr_layer.weight.data += alpha * torch.mm(_lowerCamelCase,  _lowerCamelCase				)

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

		return pipeline


if __name__ == "__main__":
						__A   :  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=0.75, 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.)')

						__A   :  Optional[Any]					=      parser.parse_args()

						__A   :  Any					=      args.base_model_path
						__A   :  Any					=      args.checkpoint_path
						__A   :  Optional[int]					=      args.dump_path
						__A   :  Optional[Any]					=      args.lora_prefix_unet
						__A   :  str					=      args.lora_prefix_text_encoder
						__A   :  str					=      args.alpha

						__A   :  int					=      convert(base_model_path, checkpoint_path, lora_prefix_unet, lora_prefix_text_encoder, alpha)

						__A   :  int					=      pipe.to(args.device)
						pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)






"""simple docstring"""







import unittest

from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate

def 						snake_case__       (					_lowerCamelCase				)			->Dict:






		"""simple docstring"""


		return x + 2





class       lowerCAmelCase__       (			unittest.TestCase    ):


				"""simple docstring"""





				def       snake_case    (     self					:	List[str]						):
						__lowercase				:		List[Any]												=				"x = 3"
						__lowercase				:		Optional[int]												=				{}
						__lowercase				:		List[Any]												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						assert result == 3
						self.assertDictEqual(lowercase__    ,   {"x": 3}						)

						__lowercase				:		Optional[int]												=				"x = y"
						__lowercase				:		Union[str, Any]												=				{"y": 5}
						__lowercase				:		str												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						# evaluate returns the value of the last assignment.
						assert result == 5
						self.assertDictEqual(lowercase__    ,   {"x": 5, "y": 5}						)



				def       snake_case    (     self					:	Dict						):
						__lowercase				:		Dict												=				"y = add_two(x)"
						__lowercase				:		List[Any]												=				{"x": 3}
						__lowercase				:		Optional[int]												=				evaluate(lowercase__    ,   {"add_two": add_two}    ,   state=lowercase__						)
						assert result == 5
						self.assertDictEqual(lowercase__    ,   {"x": 3, "y": 5}						)

						# Won't work without the tool
						with CaptureStdout() as out:
								__lowercase				:		Any												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						assert result is None
						assert "tried to execute add_two" in out.out



				def       snake_case    (     self					:	Any						):
						__lowercase				:		Optional[Any]												=				"x = 3"
						__lowercase				:		List[Any]												=				{}
						__lowercase				:		Dict												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						assert result == 3
						self.assertDictEqual(lowercase__    ,   {"x": 3}						)



				def       snake_case    (     self					:	str						):
						__lowercase				:		Optional[int]												=				"test_dict = {'x': x, 'y': add_two(x)}"
						__lowercase				:		List[str]												=				{"x": 3}
						__lowercase				:		Tuple												=				evaluate(lowercase__    ,   {"add_two": add_two}    ,   state=lowercase__						)
						self.assertDictEqual(lowercase__    ,   {"x": 3, "y": 5}						)
						self.assertDictEqual(lowercase__    ,   {"x": 3, "test_dict": {"x": 3, "y": 5}}						)



				def       snake_case    (     self					:	int						):
						__lowercase				:		Tuple												=				"x = 3\ny = 5"
						__lowercase				:		Optional[Any]												=				{}
						__lowercase				:		List[Any]												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						# evaluate returns the value of the last assignment.
						assert result == 5
						self.assertDictEqual(lowercase__    ,   {"x": 3, "y": 5}						)



				def       snake_case    (     self					:	Any						):
						__lowercase				:		str												=				"text = f'This is x: {x}.'"
						__lowercase				:		Any												=				{"x": 3}
						__lowercase				:		List[Any]												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						# evaluate returns the value of the last assignment.
						assert result == "This is x: 3."
						self.assertDictEqual(lowercase__    ,   {"x": 3, "text": "This is x: 3."}						)



				def       snake_case    (     self					:	str						):
						__lowercase				:		Optional[Any]												=				"if x <= 3:\n    y = 2\nelse:\n    y = 5"
						__lowercase				:		int												=				{"x": 3}
						__lowercase				:		Optional[int]												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						# evaluate returns the value of the last assignment.
						assert result == 2
						self.assertDictEqual(lowercase__    ,   {"x": 3, "y": 2}						)

						__lowercase				:		Optional[int]												=				{"x": 8}
						__lowercase				:		Union[str, Any]												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						# evaluate returns the value of the last assignment.
						assert result == 5
						self.assertDictEqual(lowercase__    ,   {"x": 8, "y": 5}						)



				def       snake_case    (     self					:	Dict						):
						__lowercase				:		Optional[Any]												=				"test_list = [x, add_two(x)]"
						__lowercase				:		str												=				{"x": 3}
						__lowercase				:		Any												=				evaluate(lowercase__    ,   {"add_two": add_two}    ,   state=lowercase__						)
						self.assertListEqual(lowercase__    ,   [3, 5]						)
						self.assertDictEqual(lowercase__    ,   {"x": 3, "test_list": [3, 5]}						)



				def       snake_case    (     self					:	Optional[int]						):
						__lowercase				:		str												=				"y = x"
						__lowercase				:		str												=				{"x": 3}
						__lowercase				:		int												=				evaluate(lowercase__    ,   {}    ,   state=lowercase__						)
						assert result == 3
						self.assertDictEqual(lowercase__    ,   {"x": 3, "y": 3}						)



				def       snake_case    (     self					:	Optional[int]						):
						__lowercase				:		str												=				"test_list = [x, add_two(x)]\ntest_list[1]"
						__lowercase				:		Optional[Any]												=				{"x": 3}
						__lowercase				:		Any												=				evaluate(lowercase__    ,   {"add_two": add_two}    ,   state=lowercase__						)
						assert result == 5
						self.assertDictEqual(lowercase__    ,   {"x": 3, "test_list": [3, 5]}						)

						__lowercase				:		Tuple												=				"test_dict = {'x': x, 'y': add_two(x)}\ntest_dict['y']"
						__lowercase				:		Union[str, Any]												=				{"x": 3}
						__lowercase				:		Tuple												=				evaluate(lowercase__    ,   {"add_two": add_two}    ,   state=lowercase__						)
						assert result == 5
						self.assertDictEqual(lowercase__    ,   {"x": 3, "test_dict": {"x": 3, "y": 5}}						)



				def       snake_case    (     self					:	Dict						):
						__lowercase				:		Dict												=				"x = 0\nfor i in range(3):\n    x = i"
						__lowercase				:		str												=				{}
						__lowercase				:		int												=				evaluate(lowercase__    ,   {"range": range}    ,   state=lowercase__						)
						assert result == 2
						self.assertDictEqual(lowercase__    ,   {"x": 2, "i": 2}						)
