






import argparse

import torch
from safetensors.torch import load_file

from diffusers import StableDiffusionPipeline






def 	UpperCamelCase	(							snake_case__  : Optional[Any]						,snake_case__  : int						,snake_case__  : Dict						,snake_case__  : Any						,snake_case__  : int	):




     '''simple docstring'''






     __snake_case      :Union[str, Any] 							=    StableDiffusionPipeline.from_pretrained(lowerCAmelCase_						,torch_dtype=torch.floataa	)

     # load LoRA weight from .safetensors
     __snake_case      :Tuple 							=    load_file(lowerCAmelCase_	)

     __snake_case      :List[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:
               __snake_case      :Dict 							=    key.split("""."""	)[0].split(LORA_PREFIX_TEXT_ENCODER + """_"""	)[-1].split("""_"""	)
               __snake_case      :Tuple 							=    pipeline.text_encoder
          else:
               __snake_case      :str 							=    key.split("""."""	)[0].split(LORA_PREFIX_UNET + """_"""	)[-1].split("""_"""	)
               __snake_case      :Union[str, Any] 							=    pipeline.unet

          # find the target layer
          __snake_case      :Optional[int] 							=    layer_infos.pop(0	)
          while len(lowerCAmelCase_	) > -1:
               try:
                    __snake_case      :int 							=    curr_layer.__getattr__(lowerCAmelCase_	)
                    if len(lowerCAmelCase_	) > 0:
                         __snake_case      :Any 							=    layer_infos.pop(0	)
                    elif len(lowerCAmelCase_	) == 0:
                         break
               except Exception:
                    if len(lowerCAmelCase_	) > 0:
                         temp_name += "_" + layer_infos.pop(0	)
                    else:
                         __snake_case      :Optional[int] 							=    layer_infos.pop(0	)

          __snake_case      :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:
               __snake_case      :List[Any] 							=    state_dict[pair_keys[0]].squeeze(3	).squeeze(2	).to(torch.floataa	)
               __snake_case      :Optional[Any] 							=    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:
               __snake_case      :Any 							=    state_dict[pair_keys[0]].to(torch.floataa	)
               __snake_case      :List[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__":
     lowerCamelCase__       		=  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.)""")

     lowerCamelCase__       		=  parser.parse_args()

     lowerCamelCase__       		=  args.base_model_path
     lowerCamelCase__       		=  args.checkpoint_path
     lowerCamelCase__       		=  args.dump_path
     lowerCamelCase__       		=  args.lora_prefix_unet
     lowerCamelCase__       		=  args.lora_prefix_text_encoder
     lowerCamelCase__       		=  args.alpha

     lowerCamelCase__       		=  convert(base_model_path, checkpoint_path, lora_prefix_unet, lora_prefix_text_encoder, alpha)

     lowerCamelCase__       		=  pipe.to(args.device)
     pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)






import argparse
import os
import re

import packaging.version


__a	 =      """examples/"""
__a	 =      {
    """examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
    """init""": (re.compile(R"""^__version__\s+=\s+\"([^\"]+)\"\s*$""", re.MULTILINE), """__version__ = \"VERSION\"\n"""),
    """setup""": (re.compile(R"""^(\s*)version\s*=\s*\"[^\"]+\",""", re.MULTILINE), R"""\1version=\"VERSION\","""),
    """doc""": (re.compile(R"""^(\s*)release\s*=\s*\"[^\"]+\"$""", re.MULTILINE), """release = \"VERSION\"\n"""),
}
__a	 =      {
    """init""": """src/diffusers/__init__.py""",
    """setup""": """setup.py""",
}
__a	 =      """README.md"""
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_	,    lowerCAmelCase_ )    ->Optional[Any]:
   with open(lowerCAmelCase_	,    """r"""	,    encoding="""utf-8"""	,    newline="""\n""" ) as f:
      UpperCAmelCase      					=  f.read()
   UpperCAmelCase					,	UpperCAmelCase      					=  REPLACE_PATTERNS[pattern]
   UpperCAmelCase      					=  replace.replace("""VERSION"""	,    lowerCAmelCase_ )
   UpperCAmelCase      					=  re_pattern.sub(lowerCAmelCase_	,    lowerCAmelCase_ )
   with open(lowerCAmelCase_	,    """w"""	,    encoding="""utf-8"""	,    newline="""\n""" ) as f:
      f.write(lowerCAmelCase_ )
def 	_UpperCamelCase					(    lowerCAmelCase_ )    ->int:
   for folder, directories, fnames in os.walk(lowerCAmelCase_ ):
      # Removing some of the folders with non-actively maintained examples from the walk
      if "research_projects" in directories:
         directories.remove("""research_projects""" )
      if "legacy" in directories:
         directories.remove("""legacy""" )
      for fname in fnames:
         if fname.endswith(""".py""" ):
            update_version_in_file(os.path.join(lowerCAmelCase_	,    lowerCAmelCase_ )	,    lowerCAmelCase_	,    pattern="""examples""" )
def 	_UpperCamelCase					(    lowerCAmelCase_	,    lowerCAmelCase_=False )    ->Optional[int]:
   for pattern, fname in REPLACE_FILES.items():
      update_version_in_file(lowerCAmelCase_	,    lowerCAmelCase_	,    lowerCAmelCase_ )
   if not patch:
      update_version_in_examples(lowerCAmelCase_ )
def 	_UpperCamelCase					(    )    ->List[str]:
   UpperCAmelCase      					=  """🤗 Transformers currently provides the following architectures"""
   UpperCAmelCase      					=  """1. Want to contribute a new model?"""
   with open(lowerCAmelCase_	,    """r"""	,    encoding="""utf-8"""	,    newline="""\n""" ) as f:
      UpperCAmelCase      					=  f.readlines()

   # Find the start of the list.
   UpperCAmelCase      					=  0
   while not lines[start_index].startswith(_start_prompt ):
      start_index += 1
   start_index += 1

   UpperCAmelCase      					=  start_index
   # Update the lines in the model list.
   while not lines[index].startswith(_end_prompt ):
      if lines[index].startswith("""1.""" ):
         UpperCAmelCase      					=  lines[index].replace(
             """https://huggingface.co/docs/diffusers/main/model_doc"""	,    """https://huggingface.co/docs/diffusers/model_doc"""	,    )
      index += 1

   with open(lowerCAmelCase_	,    """w"""	,    encoding="""utf-8"""	,    newline="""\n""" ) as f:
      f.writelines(lowerCAmelCase_ )
def 	_UpperCamelCase					(    )    ->List[str]:
   with open(REPLACE_FILES["""init"""]	,    """r""" ) as f:
      UpperCAmelCase      					=  f.read()
   UpperCAmelCase      					=  REPLACE_PATTERNS["""init"""][0].search(lowerCAmelCase_ ).groups()[0]
   return packaging.version.parse(lowerCAmelCase_ )
def 	_UpperCamelCase					(    lowerCAmelCase_=False )    ->int:
   UpperCAmelCase      					=  get_version()
   if patch and default_version.is_devrelease:
      raise ValueError("""Can't create a patch version from the dev branch, checkout a released version!""" )
   if default_version.is_devrelease:
      UpperCAmelCase      					=  default_version.base_version
   elif patch:
      UpperCAmelCase      					=  F"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
   else:
      UpperCAmelCase      					=  F"""{default_version.major}.{default_version.minor + 1}.0"""

   # Now let's ask nicely if that's the right one.
   UpperCAmelCase      					=  input(F"""Which version are you releasing? [{default_version}]""" )
   if len(lowerCAmelCase_ ) == 0:
      UpperCAmelCase      					=  default_version

   print(F"""Updating version to {version}.""" )
   global_version_update(lowerCAmelCase_	,    patch=lowerCAmelCase_ )
def 	_UpperCamelCase					(    )    ->int:
   UpperCAmelCase      					=  get_version()
   UpperCAmelCase      					=  F"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
   UpperCAmelCase      					=  current_version.base_version

   # Check with the user we got that right.
   UpperCAmelCase      					=  input(F"""Which version are we developing now? [{dev_version}]""" )
   if len(lowerCAmelCase_ ) == 0:
      UpperCAmelCase      					=  dev_version

   print(F"""Updating version to {version}.""" )
   global_version_update(lowerCAmelCase_ )


#    print("Cleaning main README, don't forget to run `make fix-copies`.")
#    clean_main_ref_in_model_list()


if __name__ == "__main__":
 __a	 =      argparse.ArgumentParser()
 parser.add_argument("""--post_release""", action="""store_true""", help="""Whether this is pre or post release.""")
 parser.add_argument("""--patch""", action="""store_true""", help="""Whether or not this is a patch release.""")
 __a	 =      parser.parse_args()
 if not args.post_release:
  pre_release_work(patch=args.patch)
 elif args.patch:
  print("""Nothing to do after a patch :-)""")
 else:
  post_release_work()



