






import argparse

import torch

from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging


logging.set_verbosity_info()
lowerCamelCase__       		=  logging.get_logger(__name__)

lowerCamelCase__       		=  [
    ["""attention""", """attn"""],
    ["""encoder_attention""", """encoder_attn"""],
    ["""q_lin""", """q_proj"""],
    ["""k_lin""", """k_proj"""],
    ["""v_lin""", """v_proj"""],
    ["""out_lin""", """out_proj"""],
    ["""norm_embeddings""", """layernorm_embedding"""],
    ["""position_embeddings""", """embed_positions"""],
    ["""embeddings""", """embed_tokens"""],
    ["""ffn.lin""", """fc"""],
]






def 	UpperCamelCase	(							snake_case__  : Dict	):




     '''simple docstring'''






     if k == "embeddings.weight":
          return "shared.weight"

     for parlai_name, hf_name in PATTERNS:
          __snake_case      :Union[str, Any] 							=    k.replace(lowerCAmelCase_						,lowerCAmelCase_	)

     if k.startswith("""encoder"""	):
          __snake_case      :Union[str, Any] 							=    k.replace(""".attn"""						,""".self_attn"""	)
          __snake_case      :str 							=    k.replace("""norm1"""						,"""self_attn_layer_norm"""	)
          __snake_case      :Optional[Any] 							=    k.replace("""norm2"""						,"""final_layer_norm"""	)
     elif k.startswith("""decoder"""	):
          __snake_case      :Optional[int] 							=    k.replace("""norm1"""						,"""self_attn_layer_norm"""	)
          __snake_case      :List[str] 							=    k.replace("""norm2"""						,"""encoder_attn_layer_norm"""	)
          __snake_case      :List[Any] 							=    k.replace("""norm3"""						,"""final_layer_norm"""	)
     return k






def 	UpperCamelCase	(							snake_case__  : List[Any]	):




     '''simple docstring'''






     __snake_case      :Any 							=    [
         """model.encoder.layernorm_embedding.weight""",
         """model.encoder.layernorm_embedding.bias""",
         """model.decoder.layernorm_embedding.weight""",
         """model.decoder.layernorm_embedding.bias""",
     ]
     for k in keys:
          __snake_case      :List[str] 							=    sd.pop(lowerCAmelCase_	)
          __snake_case      :List[Any] 							=    k.replace("""layernorm_embedding"""						,"""layer_norm"""	)
          assert new_k not in sd
          __snake_case      :Tuple 							=    v


lowerCamelCase__       		=  ["""START"""]






@torch.no_grad()
def 	UpperCamelCase	(							snake_case__  : Union[str, Any]						,snake_case__  : Optional[Any]						,snake_case__  : Optional[int]	):




     '''simple docstring'''






     __snake_case      :Optional[Any] 							=    torch.load(lowerCAmelCase_						,map_location="""cpu"""	)
     __snake_case      :Any 							=    model["""model"""]
     __snake_case      :List[str] 							=    BlenderbotConfig.from_json_file(lowerCAmelCase_	)
     __snake_case      :List[str] 							=    BlenderbotForConditionalGeneration(lowerCAmelCase_	)
     __snake_case      :Tuple 							=    m.model.state_dict().keys()
     __snake_case      :Dict 							=    []
     __snake_case      :Optional[int] 							=    {}
     for k, v in sd.items():
          if k in IGNORE_KEYS:
               continue

          __snake_case      :List[Any] 							=    rename_state_dict_key(lowerCAmelCase_	)
          if new_k not in valid_keys:
               failures.append([k, new_k]	)
          else:
               __snake_case      :Dict 							=    v
     if cfg.normalize_before:  # Blenderbot-3B checkpoints. Rename layernorm_embedding -> layer_norm
          rename_layernorm_keys(lowerCAmelCase_	)
     m.model.load_state_dict(lowerCAmelCase_						,strict=lowerCAmelCase_	)
     m.half()
     m.save_pretrained(lowerCAmelCase_	)


if __name__ == "__main__":
     lowerCamelCase__       		=  argparse.ArgumentParser()
     # Required parameters
     parser.add_argument("""--src_path""", type=str, help="""like blenderbot-model.bin""")
     parser.add_argument("""--save_dir""", default="""hf_blenderbot""", type=str, help="""Where to save converted model.""")
     parser.add_argument(
         """--hf_config_json""", default="""blenderbot-3b-config.json""", type=str, help="""Path to config to use"""
     )
     lowerCamelCase__       		=  parser.parse_args()
     convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)






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()



