




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


snake_case_ : List[str]    		=       logging.get_logger(__name__)

snake_case_ : Any    		=       {
    'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
    'tiiuae/falcon-7b': 'https://huggingface.co/tiiuae/falcon-7b/resolve/main/config.json',
}







class __snake_case			(			a		):
   UpperCAmelCase__  :    Union[str, Any]          =  '''falcon'''
   UpperCAmelCase__  :    int          =  ['''past_key_values''']







   def __init__(      self		:						Union[str, Any]					,						_snake_case		:						Optional[Any]=65024					,						_snake_case		:						Tuple=4544					,						_snake_case		:						Any=32					,						_snake_case		:						List[str]=71					,						_snake_case		:						List[str]=1e-5					,						_snake_case		:						List[str]=0.0_2					,						_snake_case		:						int=True					,						_snake_case		:						int=0.0					,						_snake_case		:						Union[str, Any]=0.0					,						_snake_case		:						Optional[int]=None					,						_snake_case		:						Any=False					,						_snake_case		:						Optional[int]=False					,						_snake_case		:						str=True					,						_snake_case		:						List[str]=True					,						_snake_case		:						Tuple=False					,						_snake_case		:						List[str]=11					,						_snake_case		:						Union[str, Any]=11					,						**_snake_case		:						Dict					,						):

        """simple docstring"""


        UpperCAmelCase_          =							vocab_size
        # Backward compatibility with n_embed kwarg
        UpperCAmelCase_          =							kwargs.pop('''n_embed'''					,						_snake_case)
        UpperCAmelCase_          =							hidden_size if n_embed is None else n_embed
        UpperCAmelCase_          =							num_hidden_layers
        UpperCAmelCase_          =							num_attention_heads
        UpperCAmelCase_          =							layer_norm_epsilon
        UpperCAmelCase_          =							initializer_range
        UpperCAmelCase_          =							use_cache
        UpperCAmelCase_          =							hidden_dropout
        UpperCAmelCase_          =							attention_dropout

        UpperCAmelCase_          =							bos_token_id
        UpperCAmelCase_          =							eos_token_id
        UpperCAmelCase_          =							num_attention_heads if num_kv_heads is None else num_kv_heads
        UpperCAmelCase_          =							alibi
        UpperCAmelCase_          =							new_decoder_architecture
        UpperCAmelCase_          =							multi_query  # Ignored when new_decoder_architecture is True
        UpperCAmelCase_          =							parallel_attn
        UpperCAmelCase_          =							bias

        super().__init__(bos_token_id=_snake_case					,						eos_token_id=_snake_case					,						**_snake_case)







   @property
   def lowerCamelCase						(      self		:						Any):

        """simple docstring"""


        return self.hidden_size // self.num_attention_heads







   @property
   def lowerCamelCase						(      self		:						str):

        """simple docstring"""


        return not self.alibi











"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowerCAmelCase    :List[str]     =					logging.get_logger(__name__)

_lowerCAmelCase    :Any     =					{
    'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
    'tiiuae/falcon-7b': 'https://huggingface.co/tiiuae/falcon-7b/resolve/main/config.json',
}
class 							_UpperCAmelCase							( a      ):





     '''simple docstring'''



     a__									='''falcon'''
     a__									=['''past_key_values''']





     def __init__(					self       ,	A=6_5_0_2_4       ,	A=4_5_4_4       ,	A=3_2       ,	A=7_1       ,	A=1E-5       ,	A=0.02       ,	A=True       ,	A=0.0       ,	A=0.0       ,	A=None       ,	A=False       ,	A=False       ,	A=True       ,	A=True       ,	A=False       ,	A=1_1       ,	A=1_1       ,	**A       ,	)							->					Any:
         _UpperCAmelCase							:  int											=    vocab_size
         # Backward compatibility with n_embed kwarg
         _UpperCAmelCase							:  Optional[Any]											=    kwargs.pop('''n_embed'''       ,	A		)
         _UpperCAmelCase							:  int											=    hidden_size if n_embed is None else n_embed
         _UpperCAmelCase							:  List[str]											=    num_hidden_layers
         _UpperCAmelCase							:  Tuple											=    num_attention_heads
         _UpperCAmelCase							:  Optional[int]											=    layer_norm_epsilon
         _UpperCAmelCase							:  Tuple											=    initializer_range
         _UpperCAmelCase							:  Optional[int]											=    use_cache
         _UpperCAmelCase							:  Any											=    hidden_dropout
         _UpperCAmelCase							:  Dict											=    attention_dropout

         _UpperCAmelCase							:  Any											=    bos_token_id
         _UpperCAmelCase							:  List[Any]											=    eos_token_id
         _UpperCAmelCase							:  Tuple											=    num_attention_heads if num_kv_heads is None else num_kv_heads
         _UpperCAmelCase							:  Dict											=    alibi
         _UpperCAmelCase							:  Optional[int]											=    new_decoder_architecture
         _UpperCAmelCase							:  str											=    multi_query  # Ignored when new_decoder_architecture is True
         _UpperCAmelCase							:  Optional[int]											=    parallel_attn
         _UpperCAmelCase							:  Optional[int]											=    bias

         super().__init__(bos_token_id=A       ,	eos_token_id=A       ,	**A		)





     @property
     def  __lowerCAmelCase	(					self		)							->					List[str]:
         return self.hidden_size // self.num_attention_heads





     @property
     def  __lowerCAmelCase	(					self		)							->					List[Any]:
         return not self.alibi


