from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_           =				logging.get_logger(__name__)

UpperCAmelCase_           =				{}




class 			__magic_name__	(		__a     ):





   """simple docstring"""




   lowerCAmelCase   :     List[str]	      = '''llama'''
   lowerCAmelCase   :     str	      = ['''past_key_values''']



   def __init__(						self       :	Dict		,	_lowercase       :	int=32_000		,	_lowercase       :	Dict=4_096		,	_lowercase       :	Dict=11_008		,	_lowercase       :	List[str]=32		,	_lowercase       :	str=32		,	_lowercase       :	Optional[Any]=None		,	_lowercase       :	Union[str, Any]="silu"		,	_lowercase       :	Any=2_048		,	_lowercase       :	str=0.02		,	_lowercase       :	Tuple=1E-6		,	_lowercase       :	Union[str, Any]=True		,	_lowercase       :	int=0		,	_lowercase       :	Any=1		,	_lowercase       :	List[Any]=2		,	_lowercase       :	Tuple=1		,	_lowercase       :	Any=False		,	_lowercase       :	Union[str, Any]=None		,	**_lowercase       :	Optional[int]		,	):



    """simple docstring"""



    _UpperCamelCase:  List[str]    						=			vocab_size
    _UpperCamelCase:  Optional[int]    						=			max_position_embeddings
    _UpperCamelCase:  Tuple    						=			hidden_size
    _UpperCamelCase:  Dict    						=			intermediate_size
    _UpperCamelCase:  List[str]    						=			num_hidden_layers
    _UpperCamelCase:  List[Any]    						=			num_attention_heads

    # for backward compatibility
    if num_key_value_heads is None:
     _UpperCamelCase:  int    						=			num_attention_heads

    _UpperCamelCase:  Optional[Any]    						=			num_key_value_heads
    _UpperCamelCase:  Dict    						=			hidden_act
    _UpperCamelCase:  Any    						=			initializer_range
    _UpperCamelCase:  List[str]    						=			rms_norm_eps
    _UpperCamelCase:  Dict    						=			pretraining_tp
    _UpperCamelCase:  Dict    						=			use_cache
    _UpperCamelCase:  str    						=			rope_scaling
    self._rope_scaling_validation()

    super().__init__(
        pad_token_id=_lowercase		,	bos_token_id=_lowercase		,	eos_token_id=_lowercase		,	tie_word_embeddings=_lowercase		,	**_lowercase		,	)



   def 	lowerCAmelCase    (						self       :	List[Any]				):



    """simple docstring"""



    if self.rope_scaling is None:
     return

    if not isinstance(self.rope_scaling		,	_lowercase				) or len(self.rope_scaling				) != 2:
     raise ValueError(
         '''`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '''
         f"""got {self.rope_scaling}"""				)
    _UpperCamelCase:  str    						=			self.rope_scaling.get('''type'''		,	_lowercase				)
    _UpperCamelCase:  List[str]    						=			self.rope_scaling.get('''factor'''		,	_lowercase				)
    if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
     raise ValueError(
         f"""`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"""				)
    if rope_scaling_factor is None or not isinstance(_lowercase		,	_lowercase				) or rope_scaling_factor <= 1.0:
     raise ValueError(f"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"""				)
from pathlib import Path

import fire




def    lowerCAmelCase_  (		lowercase:				str	,       lowercase:				str	,       lowercase:				int		)     ->					int:







 '''simple docstring'''
 _UpperCamelCase:  Any    						=			Path(lowercase		)
 _UpperCamelCase:  int    						=			Path(lowercase		)
 dest_dir.mkdir(exist_ok=lowercase		)
 for path in src_dir.iterdir():
  _UpperCamelCase:  List[str]    						=			[x.rstrip() for x in list(path.open().readlines()		)][:n]
  _UpperCamelCase:  int    						=			dest_dir.joinpath(path.name		)
  print(lowercase		)
  dest_path.open('''w'''		).write('''\n'''.join(lowercase		)		)


if __name__ == "__main__":
  fire.Fire(minify)