






def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							int = 10					,  snake_case_ :							int = 1000					,  snake_case_ :							bool = True       ):
	assert (
	    isinstance(snake_case_					,  snake_case_       )
	    and isinstance(snake_case_					,  snake_case_       )
	    and isinstance(snake_case_					,  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 					SCREAMING_SNAKE_CASE    (			snake_case_ :							int					,  snake_case_ :							int       ):
	return int((number_a + number_a) / 2       )







def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							int					,  snake_case_ :							int					,  snake_case_ :							int       ):
	assert (
	    isinstance(snake_case_					,  snake_case_       ) and isinstance(snake_case_					,  snake_case_       ) and isinstance(snake_case_					,  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(snake_case_ :							int       ) -> str:
		if number > to_guess:
			return "high"
		elif number < to_guess:
			return "low"
		else:
			return "same"

	print("started..."       )

	snake_case__			:				Union[str, Any]       =  lower
	snake_case__			:				int       =  higher

	snake_case__			:				Tuple       =  []

	while True:
		snake_case__			:				Optional[Any]       =  get_avg(snake_case_					,  snake_case_       )
		last_numbers.append(snake_case_       )

		if answer(snake_case_       ) == "low":
			snake_case__			:				Tuple       =  number
		elif answer(snake_case_       ) == "high":
			snake_case__			:				Tuple       =  number
		else:
			break

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







def 					SCREAMING_SNAKE_CASE    (			):
	snake_case__			:				List[Any]       =  int(input("Enter lower value : "       ).strip()       )
	snake_case__			:				Dict       =  int(input("Enter high value : "       ).strip()       )
	snake_case__			:				Optional[int]       =  int(input("Enter value to guess : "       ).strip()       )
	guess_the_number(snake_case_					,  snake_case_					,  snake_case_       )


if __name__ == "__main__":
	main()











from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


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

__lowerCamelCase :      List[Any]										=				{
    """facebook/xmod-base""": """https://huggingface.co/facebook/xmod-base/resolve/main/config.json""",
    """facebook/xmod-large-prenorm""": """https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json""",
    """facebook/xmod-base-13-125k""": """https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-125k""": """https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json""",
    """facebook/xmod-base-30-195k""": """https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json""",
    """facebook/xmod-base-60-125k""": """https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json""",
    """facebook/xmod-base-60-265k""": """https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json""",
    """facebook/xmod-base-75-125k""": """https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json""",
    """facebook/xmod-base-75-269k""": """https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json""",
}



class 							SCREAMING_SNAKE_CASE__						(    UpperCamelCase_						):





					"""simple docstring"""






					a_     =		"xmod"



					def __init__( self					:  List[str]							,		__A					:  List[str]=3_0_5_2_2							,		__A					:  Tuple=7_6_8							,		__A					:  str=1_2							,		__A					:  List[Any]=1_2							,		__A					:  List[str]=3_0_7_2							,		__A					:  List[str]="gelu"							,		__A					:  List[Any]=0.1							,		__A					:  Tuple=0.1							,		__A					:  str=5_1_2							,		__A					:  Union[str, Any]=2							,		__A					:  List[Any]=0.0_2							,		__A					:  List[str]=1e-1_2							,		__A					:  Tuple=1							,		__A					:  List[Any]=0							,		__A					:  Optional[Any]=2							,		__A					:  Optional[int]="absolute"							,		__A					:  Optional[int]=True							,		__A					:  Dict=None							,		__A					:  Optional[int]=False							,		__A					:  Dict=2							,		__A					:  List[str]=False							,		__A					:  Dict=True							,		__A					:  Union[str, Any]=True							,		__A					:  Tuple=("en_XX",)							,		__A					:  Optional[Any]=None							,		**__A					:  Tuple							,		):
						super().__init__(pad_token_id=__A							,		bos_token_id=__A							,		eos_token_id=__A							,		**__A	)

						snake_case__			:				Tuple       =  vocab_size
						snake_case__			:				Union[str, Any]       =  hidden_size
						snake_case__			:				int       =  num_hidden_layers
						snake_case__			:				str       =  num_attention_heads
						snake_case__			:				Tuple       =  hidden_act
						snake_case__			:				Optional[Any]       =  intermediate_size
						snake_case__			:				List[str]       =  hidden_dropout_prob
						snake_case__			:				Optional[int]       =  attention_probs_dropout_prob
						snake_case__			:				Union[str, Any]       =  max_position_embeddings
						snake_case__			:				str       =  type_vocab_size
						snake_case__			:				List[str]       =  initializer_range
						snake_case__			:				Dict       =  layer_norm_eps
						snake_case__			:				str       =  position_embedding_type
						snake_case__			:				List[str]       =  use_cache
						snake_case__			:				Tuple       =  classifier_dropout
						snake_case__			:				Any       =  pre_norm
						snake_case__			:				List[str]       =  adapter_reduction_factor
						snake_case__			:				List[Any]       =  adapter_layer_norm
						snake_case__			:				str       =  adapter_reuse_layer_norm
						snake_case__			:				Union[str, Any]       =  ln_before_adapter
						snake_case__			:				Tuple       =  list(__A	)
						snake_case__			:				int       =  default_language



class 							SCREAMING_SNAKE_CASE__						(    UpperCamelCase_						):





					"""simple docstring"""






					@property
					def 	_lowercase					( self					:  int	):
						if self.task == "multiple-choice":
							snake_case__			:				Any       =  {0: "batch", 1: "choice", 2: "sequence"}
						else:
							snake_case__			:				Any       =  {0: "batch", 1: "sequence"}
						return OrderedDict(
						    [
						        ("input_ids", dynamic_axis),
						        ("attention_mask", dynamic_axis),
						    ]	)



