





"""simple docstring"""





import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM


def       lowerCamelCase_       (   UpperCAmelCase_  )						->List[Any]:





  """simple docstring"""


  if "model" in orig_key:
    __UpperCAmelCase    :						List[Any]       =						orig_key.replace('''model.'''  ,			''''''  )
  if "norm1" in orig_key:
    __UpperCAmelCase    :						str       =						orig_key.replace('''norm1'''  ,			'''attention.output.LayerNorm'''  )
  if "norm2" in orig_key:
    __UpperCAmelCase    :						str       =						orig_key.replace('''norm2'''  ,			'''output.LayerNorm'''  )
  if "norm" in orig_key:
    __UpperCAmelCase    :						Dict       =						orig_key.replace('''norm'''  ,			'''LayerNorm'''  )
  if "transformer" in orig_key:
    __UpperCAmelCase    :						List[Any]       =						orig_key.split('''.'''  )[0].split('''_'''  )[-1]
    __UpperCAmelCase    :						Dict       =						orig_key.replace(f'''transformer_{layer_num}'''  ,			f'''encoder.layer.{layer_num}'''  )
  if "mha.attn" in orig_key:
    __UpperCAmelCase    :						Optional[int]       =						orig_key.replace('''mha.attn'''  ,			'''attention.self'''  )
  if "mha" in orig_key:
    __UpperCAmelCase    :						Optional[Any]       =						orig_key.replace('''mha'''  ,			'''attention'''  )
  if "W_q" in orig_key:
    __UpperCAmelCase    :						int       =						orig_key.replace('''W_q'''  ,			'''self.query'''  )
  if "W_k" in orig_key:
    __UpperCAmelCase    :						Any       =						orig_key.replace('''W_k'''  ,			'''self.key'''  )
  if "W_v" in orig_key:
    __UpperCAmelCase    :						Any       =						orig_key.replace('''W_v'''  ,			'''self.value'''  )
  if "ff1" in orig_key:
    __UpperCAmelCase    :						Optional[Any]       =						orig_key.replace('''ff1'''  ,			'''intermediate.dense'''  )
  if "ff2" in orig_key:
    __UpperCAmelCase    :						Union[str, Any]       =						orig_key.replace('''ff2'''  ,			'''output.dense'''  )
  if "ff" in orig_key:
    __UpperCAmelCase    :						List[str]       =						orig_key.replace('''ff'''  ,			'''output.dense'''  )
  if "mlm_class" in orig_key:
    __UpperCAmelCase    :						Optional[int]       =						orig_key.replace('''mlm.mlm_class'''  ,			'''cls.predictions.decoder'''  )
  if "mlm" in orig_key:
    __UpperCAmelCase    :						int       =						orig_key.replace('''mlm'''  ,			'''cls.predictions.transform'''  )
  if "cls" not in orig_key:
    __UpperCAmelCase    :						Optional[Any]       =						'''yoso.''' + orig_key

  return orig_key


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->Optional[int]:





  """simple docstring"""


  for key in orig_state_dict.copy().keys():
    __UpperCAmelCase    :						Optional[int]       =						orig_state_dict.pop(SCREAMING_SNAKE_CASE_  )

    if ("pooler" in key) or ("sen_class" in key):
      continue
    else:
      __UpperCAmelCase    :						List[str]       =						val

  __UpperCAmelCase    :						Optional[Any]       =						orig_state_dict['''cls.predictions.decoder.bias''']
  __UpperCAmelCase    :						Tuple       =						torch.arange(SCREAMING_SNAKE_CASE_  ).expand((1, -1)  ) + 2

  return orig_state_dict


def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  )						->Union[str, Any]:





  """simple docstring"""


  __UpperCAmelCase    :						Dict       =						torch.load(SCREAMING_SNAKE_CASE_  ,			map_location='''cpu'''  )['''model_state_dict''']
  __UpperCAmelCase    :						Optional[Any]       =						YosoConfig.from_json_file(SCREAMING_SNAKE_CASE_  )
  __UpperCAmelCase    :						str       =						YosoForMaskedLM(SCREAMING_SNAKE_CASE_  )

  __UpperCAmelCase    :						List[Any]       =						convert_checkpoint_helper(config.max_position_embeddings  ,			SCREAMING_SNAKE_CASE_  )

  print(model.load_state_dict(SCREAMING_SNAKE_CASE_  )  )
  model.eval()
  model.save_pretrained(SCREAMING_SNAKE_CASE_  )

  print(f'''Checkpoint successfuly converted. Model saved at {pytorch_dump_path}'''  )


if __name__ == "__main__":
  __snake_case				:int				   =       argparse.ArgumentParser()
  # Required parameters
  parser.add_argument(
      '--pytorch_model_path', default=None, type=str, required=True, help='Path to YOSO pytorch checkpoint.'
  )
  parser.add_argument(
      '--config_file',
      default=None,
      type=str,
      required=True,
      help='The json file for YOSO model config.',
  )
  parser.add_argument(
      '--pytorch_dump_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
  )
  __snake_case				:int				   =       parser.parse_args()
  convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)






"""simple docstring"""





def       lowerCamelCase_       (   UpperCAmelCase_  ,			UpperCAmelCase_  )						->bool:





  """simple docstring"""


  return numa ^ numa < 0


if __name__ == "__main__":
  import doctest

  doctest.testmod()