





'''simple docstring'''






import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM
def    UpperCamelCase__      (		lowerCAmelCase  ):





      """simple docstring"""


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

      return orig_key
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      for key in orig_state_dict.copy().keys():
            _lowerCAmelCase							     =							orig_state_dict.pop(_lowercase  )

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

      _lowerCAmelCase							     =							orig_state_dict["cls.predictions.decoder.bias"]
      _lowerCAmelCase							     =							torch.arange(_lowercase  ).expand((1, -1)  ) + 2

      return orig_state_dict
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							torch.load(_lowercase							,	map_location="""cpu"""  )["model_state_dict"]
      _lowerCAmelCase							     =							YosoConfig.from_json_file(_lowercase  )
      _lowerCAmelCase							     =							YosoForMaskedLM(_lowercase  )

      _lowerCAmelCase							     =							convert_checkpoint_helper(config.max_position_embeddings							,	_lowercase  )

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

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


if __name__ == "__main__":
      A__				:   Tuple      =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.'''
      )
      A__				:   Tuple      =parser.parse_args()
      convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)













"""simple docstring"""




from unittest.mock import Mock, patch

from file_transfer.send_file import send_file






@patch("socket.socket"					)
@patch("builtins.open"					)
def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    List[Any]    ,       _lowercase						:    int					) ->str:






	'''simple docstring'''






	a      :		Optional[Any]	=				Mock()
	a      :		Dict	=				conn, Mock()
	a      :		Union[str, Any]	=				iter([1, None]					)
	a      :		Optional[int]	=				lambda _lowercase					: next(_lowercase					)

	# ===== invoke =====
	send_file(filename="mytext.txt"    ,       testing=_lowercase					)

	# ===== ensurance =====
	sock.assert_called_once()
	sock.return_value.bind.assert_called_once()
	sock.return_value.listen.assert_called_once()
	sock.return_value.accept.assert_called_once()
	conn.recv.assert_called_once()

	file.return_value.__enter__.assert_called_once()
	file.return_value.__enter__.return_value.read.assert_called()

	conn.send.assert_called_once()
	conn.close.assert_called_once()
	sock.return_value.shutdown.assert_called_once()
	sock.return_value.close.assert_called_once()


