






import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM

def   __lowercase       (			snake_case			):







				"""simple docstring"""






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

				return orig_key

def   __lowercase       (			snake_case,	snake_case			):







				"""simple docstring"""






				for key in orig_state_dict.copy().keys():
								__magic_name__		:Any   =   orig_state_dict.pop(snake_case			)

								if ("pooler" in key) or ("sen_class" in key):
												continue
								else:
												__magic_name__		:int   =   val

				__magic_name__		:Any   =   orig_state_dict['''cls.predictions.decoder.bias''']
				__magic_name__		:Union[str, Any]   =   torch.arange(snake_case			).expand((1, -1)			) + 2

				return orig_state_dict

def   __lowercase       (			snake_case,	snake_case,	snake_case			):







				"""simple docstring"""






				__magic_name__		:Optional[Any]   =   torch.load(snake_case,	map_location='''cpu'''			)['''model_state_dict''']
				__magic_name__		:Optional[int]   =   YosoConfig.from_json_file(snake_case			)
				__magic_name__		:str   =   YosoForMaskedLM(snake_case			)

				__magic_name__		:str   =   convert_checkpoint_helper(config.max_position_embeddings,	snake_case			)

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

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


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__   :      Union[str, Any]				=		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."""
					)
					SCREAMING_SNAKE_CASE__   :      List[str]				=		parser.parse_args()
					convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)












'''simple docstring'''





from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version





def       __a      (  _UpperCamelCase:       str   ,		_UpperCamelCase:       str   ,		_UpperCamelCase:       Optional[str] = None       )		->					str:

     """simple docstring"""




     if version.parse(hfh.__version__       ).release < version.parse("0.11.0"       ).release:
          # old versions of hfh don't url-encode the file path
          _snake_case				= quote(_UpperCamelCase       )
     return hfh.hf_hub_url(_UpperCamelCase   ,		_UpperCamelCase   ,		repo_type="dataset"   ,		revision=_UpperCamelCase       )


