



'''simple docstring'''

def       __lowercase  (_SCREAMING_SNAKE_CASE      :int = 10    ,	_SCREAMING_SNAKE_CASE      :int = 10_00    ,	_SCREAMING_SNAKE_CASE      :bool = True       ):
				assert (
				    isinstance(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
				    and isinstance(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
				    and isinstance(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
				), "Invalid type of value(s) specified to function!"

				if min_val > max_val:
								raise ValueError('''Invalid value for min_val or max_val (min_value < max_value)'''       )
				return min_val if option else max_val






def       __lowercase  (_SCREAMING_SNAKE_CASE      :int    ,	_SCREAMING_SNAKE_CASE      :int       ):
				return int((number_a + number_a) / 2       )






def       __lowercase  (_SCREAMING_SNAKE_CASE      :int    ,	_SCREAMING_SNAKE_CASE      :int    ,	_SCREAMING_SNAKE_CASE      :int       ):
				assert (
				    isinstance(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       ) and isinstance(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       ) and isinstance(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
				), 'argument values must be type of "int"'

				if lower > higher:
								raise ValueError('''argument value for lower and higher must be(lower > higher)'''       )

				if not lower < to_guess < higher:
								raise ValueError(
								    '''guess value must be within the range of lower and higher value'''       )

				def answer(_SCREAMING_SNAKE_CASE      :int       ) -> str:
								if number > to_guess:
												return "high"
								elif number < to_guess:
												return "low"
								else:
												return "same"

				print('''started...'''       )

				SCREAMING_SNAKE_CASE  :						List[str]      					= lower
				SCREAMING_SNAKE_CASE  :						Any      					= higher

				SCREAMING_SNAKE_CASE  :						List[Any]      					= []

				while True:
								SCREAMING_SNAKE_CASE  :						int      					= get_avg(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )
								last_numbers.append(_SCREAMING_SNAKE_CASE       )

								if answer(_SCREAMING_SNAKE_CASE       ) == "low":
												SCREAMING_SNAKE_CASE  :						List[Any]      					= number
								elif answer(_SCREAMING_SNAKE_CASE       ) == "high":
												SCREAMING_SNAKE_CASE  :						Optional[Any]      					= number
								else:
												break

				print(F'''guess the number : {last_numbers[-1]}'''       )
				print(F'''details : {last_numbers!s}'''       )






def       __lowercase  ():
				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= int(input('''Enter lower value : '''       ).strip()       )
				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= int(input('''Enter high value : '''       ).strip()       )
				SCREAMING_SNAKE_CASE  :						Any      					= int(input('''Enter value to guess : '''       ).strip()       )
				guess_the_number(_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE    ,	_SCREAMING_SNAKE_CASE       )


if __name__ == "__main__":
	main()









'''simple docstring'''

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


snake_case_			=     logging.get_logger(__name__)

snake_case_			=     {
    """facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}


class 	a__     (				_lowercase	):
	__magic_name__		:    Optional[Any]	    =     "nllb-moe"
	__magic_name__		:    Optional[Any]	    =     ["past_key_values"]
	__magic_name__		:    Optional[int]	    =     {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}


	def __init__(self : int,					__UpperCAmelCase : Tuple=128112,					__UpperCAmelCase : Any=1024,					__UpperCAmelCase : Optional[Any]=12,					__UpperCAmelCase : Optional[int]=4096,					__UpperCAmelCase : Any=16,					__UpperCAmelCase : Any=12,					__UpperCAmelCase : Optional[Any]=4096,					__UpperCAmelCase : Optional[int]=16,					__UpperCAmelCase : List[Any]=0.05,					__UpperCAmelCase : Dict=0.05,					__UpperCAmelCase : Dict=True,					__UpperCAmelCase : List[Any]=True,					__UpperCAmelCase : Any="relu",					__UpperCAmelCase : Union[str, Any]=1024,					__UpperCAmelCase : Optional[int]=0.1,					__UpperCAmelCase : Tuple=0.1,					__UpperCAmelCase : List[Any]=0.0,					__UpperCAmelCase : Optional[int]=0.02,					__UpperCAmelCase : Tuple=2,					__UpperCAmelCase : int=True,					__UpperCAmelCase : int=False,					__UpperCAmelCase : int="float32",					__UpperCAmelCase : Optional[Any]=False,					__UpperCAmelCase : List[str]=128,					__UpperCAmelCase : Dict=64,					__UpperCAmelCase : Dict=4,					__UpperCAmelCase : Optional[Any]=4,					__UpperCAmelCase : Optional[Any]=0.001,					__UpperCAmelCase : Optional[Any]=0.001,					__UpperCAmelCase : Optional[Any]="all",					__UpperCAmelCase : List[str]=False,					__UpperCAmelCase : Dict=False,					__UpperCAmelCase : Any=1.0,					__UpperCAmelCase : Dict=0.2,					__UpperCAmelCase : int=1,					__UpperCAmelCase : Union[str, Any]=0,					__UpperCAmelCase : Any=2,					__UpperCAmelCase : Union[str, Any]=False,					**__UpperCAmelCase : Dict,					)     ->			List[Any]:

					"""simple docstring"""

					SCREAMING_SNAKE_CASE  :						Any      					= vocab_size
					SCREAMING_SNAKE_CASE  :						int      					= max_position_embeddings
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= d_model
					SCREAMING_SNAKE_CASE  :						Dict      					= encoder_ffn_dim
					SCREAMING_SNAKE_CASE  :						int      					= encoder_layers
					SCREAMING_SNAKE_CASE  :						str      					= encoder_attention_heads
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= decoder_ffn_dim
					SCREAMING_SNAKE_CASE  :						str      					= decoder_layers
					SCREAMING_SNAKE_CASE  :						Dict      					= decoder_attention_heads
					SCREAMING_SNAKE_CASE  :						Dict      					= dropout
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= attention_dropout
					SCREAMING_SNAKE_CASE  :						Dict      					= activation_dropout
					SCREAMING_SNAKE_CASE  :						List[str]      					= activation_function
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= init_std
					SCREAMING_SNAKE_CASE  :						Any      					= encoder_layerdrop
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= decoder_layerdrop
					SCREAMING_SNAKE_CASE  :						Dict      					= use_cache
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= encoder_layers
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= scale_embedding  # scale factor will be sqrt(d_model) if True
					SCREAMING_SNAKE_CASE  :						List[str]      					= router_z_loss_coef
					SCREAMING_SNAKE_CASE  :						List[str]      					= router_aux_loss_coef
					SCREAMING_SNAKE_CASE  :						int      					= decoder_sparse_step
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= encoder_sparse_step
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= num_experts
					SCREAMING_SNAKE_CASE  :						List[Any]      					= expert_capacity
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= router_bias
					if router_dtype not in ["float32", "float16", "bfloat16"]:
									raise ValueError(F'''`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'''      )
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= router_dtype

					SCREAMING_SNAKE_CASE  :						int      					= router_ignore_padding_tokens
					SCREAMING_SNAKE_CASE  :						Dict      					= batch_prioritized_routing
					SCREAMING_SNAKE_CASE  :						Dict      					= second_expert_policy
					SCREAMING_SNAKE_CASE  :						Tuple      					= normalize_router_prob_before_dropping
					SCREAMING_SNAKE_CASE  :						List[str]      					= moe_eval_capacity_token_fraction
					SCREAMING_SNAKE_CASE  :						List[Any]      					= moe_token_dropout
					SCREAMING_SNAKE_CASE  :						List[Any]      					= output_router_logits
					super().__init__(
					    pad_token_id=__UpperCAmelCase,					bos_token_id=__UpperCAmelCase,					eos_token_id=__UpperCAmelCase,					is_encoder_decoder=__UpperCAmelCase,					decoder_start_token_id=__UpperCAmelCase,					**__UpperCAmelCase,					)




