




from __future__ import annotations







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_				,       lowercase_		)     -> float:



       """simple docstring"""

       if days_between_payments <= 0:
              raise ValueError('''days_between_payments must be > 0'''		)
       if daily_interest_rate < 0:
              raise ValueError('''daily_interest_rate must be >= 0'''		)
       if principal <= 0:
              raise ValueError('''principal must be > 0'''		)
       return principal * daily_interest_rate * days_between_payments







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_				,       lowercase_				,       )     -> float:



       """simple docstring"""

       if number_of_compounding_periods <= 0:
              raise ValueError('''number_of_compounding_periods must be > 0'''		)
       if nominal_annual_interest_rate_percentage < 0:
              raise ValueError('''nominal_annual_interest_rate_percentage must be >= 0'''		)
       if principal <= 0:
              raise ValueError('''principal must be > 0'''		)

       return principal * (
           (1 + nominal_annual_interest_rate_percentage) ** number_of_compounding_periods
           - 1
       )







def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_				,       lowercase_				,       )     -> float:



       """simple docstring"""

       if number_of_years <= 0:
              raise ValueError('''number_of_years must be > 0'''		)
       if nominal_annual_percentage_rate < 0:
              raise ValueError('''nominal_annual_percentage_rate must be >= 0'''		)
       if principal <= 0:
              raise ValueError('''principal must be > 0'''		)

       return compound_interest(
           lowercase_				,       nominal_annual_percentage_rate / 365				,       number_of_years * 365		)


if __name__ == "__main__":
  import doctest

  doctest.testmod()








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


_lowerCamelCase			:	Tuple							 =     logging.get_logger(__name__)

_lowerCamelCase			:	Tuple							 =     {
    """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_					(				UpperCAmelCase__  ):

    '''simple docstring'''






    UpperCAmelCase__													=   '''falcon'''
    UpperCAmelCase__													=   ['''past_key_values''']


    def __init__(    self   :			Optional[Any]      ,				UpperCAmelCase__   :			str=65_024      ,				UpperCAmelCase__   :			List[Any]=4_544      ,				UpperCAmelCase__   :			Optional[Any]=32      ,				UpperCAmelCase__   :			Dict=71      ,				UpperCAmelCase__   :			Any=1e-5      ,				UpperCAmelCase__   :			Optional[int]=0.02      ,				UpperCAmelCase__   :			Optional[int]=True      ,				UpperCAmelCase__   :			Union[str, Any]=0.0      ,				UpperCAmelCase__   :			List[str]=0.0      ,				UpperCAmelCase__   :			str=None      ,				UpperCAmelCase__   :			Dict=False      ,				UpperCAmelCase__   :			List[str]=False      ,				UpperCAmelCase__   :			Optional[Any]=True      ,				UpperCAmelCase__   :			Optional[Any]=True      ,				UpperCAmelCase__   :			Optional[Any]=False      ,				UpperCAmelCase__   :			Dict=11      ,				UpperCAmelCase__   :			str=11      ,				**UpperCAmelCase__   :			Dict      ,				)		->Any:





           '''simple docstring'''

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

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

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


    @property
    def  SCREAMING_SNAKE_CASE							(    self   :			str)		->int:





           '''simple docstring'''

           return self.hidden_size // self.num_attention_heads





    @property
    def  SCREAMING_SNAKE_CASE							(    self   :			str)		->Dict:





           '''simple docstring'''

           return not self.alibi


