
def      UpperCAmelCase__				(							__magic_name__    :  int | float | str	):


					'''simple docstring'''

					try:
										lowerCAmelCase		:       int							=  float(__lowercase	)
					except ValueError:
										raise ValueError('''Please enter a valid number'''	)
					lowerCAmelCase		:       List[str]							=  decimal - int(__lowercase	)
					if fractional_part == 0:
										return int(__lowercase	), 1
					else:
										lowerCAmelCase		:       List[str]							=  len(str(__lowercase	).split('''.'''	)[1]	)
										lowerCAmelCase		:       Any							=  int(decimal * (10**number_of_frac_digits)	)
										lowerCAmelCase		:       List[str]							=  10**number_of_frac_digits
										lowerCAmelCase						,				lowerCAmelCase		:       Dict							=  denominator, numerator
										while True:
															lowerCAmelCase		:       Tuple							=  dividend % divisor
															if remainder == 0:
																				break
															lowerCAmelCase						,				lowerCAmelCase		:       Union[str, Any]							=  divisor, remainder
										lowerCAmelCase						,				lowerCAmelCase		:       Optional[Any]							=  numerator / divisor, denominator / divisor
										return int(__lowercase	), int(__lowercase	)


if __name__ == "__main__":
		print(f"""{decimal_to_fraction(2) = }""")
		print(f"""{decimal_to_fraction(89.0) = }""")
		print(f"""{decimal_to_fraction('67') = }""")
		print(f"""{decimal_to_fraction('45.0') = }""")
		print(f"""{decimal_to_fraction(1.5) = }""")
		print(f"""{decimal_to_fraction('6.25') = }""")
		print(f"""{decimal_to_fraction('78td') = }""")








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


__a   :							Dict						= logging.get_logger(__name__)

__a   :							Dict						= {
    "bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}


class    __lowercase   (						lowercase_	):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE     =					"gpt_bigcode"
     SCREAMING_SNAKE_CASE     =					["past_key_values"]
     SCREAMING_SNAKE_CASE     =					{
         "hidden_size": "n_embd",
         "max_position_embeddings": "n_positions",
         "num_attention_heads": "n_head",
         "num_hidden_layers": "n_layer",
     }




     def __init__(					self							:      List[str]			,						UpperCamelCase_							:      Dict=50_257			,						UpperCamelCase_							:      int=1_024			,						UpperCamelCase_							:      List[Any]=768			,						UpperCamelCase_							:      str=12			,						UpperCamelCase_							:      Union[str, Any]=12			,						UpperCamelCase_							:      Optional[Any]=None			,						UpperCamelCase_							:      Tuple="gelu_pytorch_tanh"			,						UpperCamelCase_							:      Optional[Any]=0.1			,						UpperCamelCase_							:      List[str]=0.1			,						UpperCamelCase_							:      Optional[int]=0.1			,						UpperCamelCase_							:      int=1e-5			,						UpperCamelCase_							:      Tuple=0.02			,						UpperCamelCase_							:      Any=True			,						UpperCamelCase_							:      List[Any]=True			,						UpperCamelCase_							:      Dict=50_256			,						UpperCamelCase_							:      Optional[Any]=50_256			,						UpperCamelCase_							:      int=True			,						UpperCamelCase_							:      List[Any]=True			,						UpperCamelCase_							:      List[Any]=True			,						**UpperCamelCase_							:      int			,						):


         """simple docstring"""



         __A       =						vocab_size
         __A       =						n_positions
         __A       =						n_embd
         __A       =						n_layer
         __A       =						n_head
         __A       =						n_inner
         __A       =						activation_function
         __A       =						resid_pdrop
         __A       =						embd_pdrop
         __A       =						attn_pdrop
         __A       =						layer_norm_epsilon
         __A       =						initializer_range
         __A       =						scale_attn_weights
         __A       =						use_cache
         __A       =						attention_softmax_in_fpaa
         __A       =						scale_attention_softmax_in_fpaa
         __A       =						multi_query

         __A       =						bos_token_id
         __A       =						eos_token_id

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




