




'''simple docstring'''





def SCREAMING_SNAKE_CASE       ( lowercase_ = 10				,       lowercase_ = 1_000				,       lowercase_ = True		)     -> Union[str, Any]:



       """simple docstring"""

       assert (
           isinstance(_A				,       _A		)
           and isinstance(_A				,       _A		)
           and isinstance(_A				,       _A		)
       ), "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       ( lowercase_				,       lowercase_		)     -> Optional[int]:



       """simple docstring"""

       return int((number_a + number_a) / 2		)







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



       """simple docstring"""

       assert (
           isinstance(_A				,       _A		) and isinstance(_A				,       _A		) and isinstance(_A				,       _A		)
       ), '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(lowercase_		) -> str:
              if number > to_guess:
                     return "high"
              elif number < to_guess:
                     return "low"
              else:
                     return "same"

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

       A__   				=					lower
       A__   				=					higher

       A__   				=					[]

       while True:
              A__   				=					get_avg(_A				,       _A		)
              last_numbers.append(_A		)

              if answer(_A		) == "low":
                     A__   				=					number
              elif answer(_A		) == "high":
                     A__   				=					number
              else:
                     break

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







def SCREAMING_SNAKE_CASE       ( )     -> Tuple:



       """simple docstring"""

       A__   				=					int(input('''Enter lower value : '''		).strip()		)
       A__   				=					int(input('''Enter high value : '''		).strip()		)
       A__   				=					int(input('''Enter value to guess : '''		).strip()		)
       guess_the_number(_A				,       _A				,       _A		)


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[Any]							 =     logging.get_logger(__name__)

_lowerCamelCase			:	Dict							 =     {
    """xlm-mlm-en-2048""": """https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json""",
    """xlm-mlm-ende-1024""": """https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-enfr-1024""": """https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json""",
    """xlm-mlm-enro-1024""": """https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json""",
    """xlm-mlm-tlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json""",
    """xlm-mlm-xnli15-1024""": """https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json""",
    """xlm-clm-enfr-1024""": """https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json""",
    """xlm-clm-ende-1024""": """https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json""",
    """xlm-mlm-17-1280""": """https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json""",
    """xlm-mlm-100-1280""": """https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json""",
}


class        UpperCamelCase_					(				UpperCAmelCase__  ):

    '''simple docstring'''






    UpperCAmelCase__													=   '''xlm'''
    UpperCAmelCase__													=   {
        '''hidden_size''': '''emb_dim''',
        '''num_attention_heads''': '''n_heads''',
        '''num_hidden_layers''': '''n_layers''',
        '''n_words''': '''vocab_size''',  # For backward compatibility
    }


    def __init__(    self   :			Tuple      ,				UpperCAmelCase__   :			Optional[Any]=30_145      ,				UpperCAmelCase__   :			List[str]=2_048      ,				UpperCAmelCase__   :			str=12      ,				UpperCAmelCase__   :			List[Any]=16      ,				UpperCAmelCase__   :			Dict=0.1      ,				UpperCAmelCase__   :			Tuple=0.1      ,				UpperCAmelCase__   :			str=True      ,				UpperCAmelCase__   :			Union[str, Any]=False      ,				UpperCAmelCase__   :			str=False      ,				UpperCAmelCase__   :			Optional[int]=False      ,				UpperCAmelCase__   :			List[str]=1      ,				UpperCAmelCase__   :			List[Any]=True      ,				UpperCAmelCase__   :			Union[str, Any]=512      ,				UpperCAmelCase__   :			List[str]=2_048**-0.5      ,				UpperCAmelCase__   :			List[Any]=1e-12      ,				UpperCAmelCase__   :			Any=0.02      ,				UpperCAmelCase__   :			str=0      ,				UpperCAmelCase__   :			int=1      ,				UpperCAmelCase__   :			Union[str, Any]=2      ,				UpperCAmelCase__   :			List[Any]=3      ,				UpperCAmelCase__   :			int=5      ,				UpperCAmelCase__   :			Any=True      ,				UpperCAmelCase__   :			Tuple="first"      ,				UpperCAmelCase__   :			Optional[int]=True      ,				UpperCAmelCase__   :			List[str]=None      ,				UpperCAmelCase__   :			Tuple=True      ,				UpperCAmelCase__   :			Dict=0.1      ,				UpperCAmelCase__   :			Any=5      ,				UpperCAmelCase__   :			List[Any]=5      ,				UpperCAmelCase__   :			int=0      ,				UpperCAmelCase__   :			Dict=0      ,				UpperCAmelCase__   :			Dict=2      ,				UpperCAmelCase__   :			str=0      ,				**UpperCAmelCase__   :			List[str]      ,				)		->str:





           '''simple docstring'''

           A__   				=					vocab_size
           A__   				=					emb_dim
           A__   				=					n_layers
           A__   				=					n_heads
           A__   				=					dropout
           A__   				=					attention_dropout
           A__   				=					gelu_activation
           A__   				=					sinusoidal_embeddings
           A__   				=					causal
           A__   				=					asm
           A__   				=					n_langs
           A__   				=					use_lang_emb
           A__   				=					layer_norm_eps
           A__   				=					bos_index
           A__   				=					eos_index
           A__   				=					pad_index
           A__   				=					unk_index
           A__   				=					mask_index
           A__   				=					is_encoder
           A__   				=					max_position_embeddings
           A__   				=					embed_init_std
           A__   				=					init_std
           A__   				=					summary_type
           A__   				=					summary_use_proj
           A__   				=					summary_activation
           A__   				=					summary_proj_to_labels
           A__   				=					summary_first_dropout
           A__   				=					start_n_top
           A__   				=					end_n_top
           A__   				=					mask_token_id
           A__   				=					lang_id

           if "n_words" in kwargs:
                  A__   				=					kwargs['''n_words''']

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


class        UpperCamelCase_					(				UpperCAmelCase__  ):

    '''simple docstring'''






    @property
    def  SCREAMING_SNAKE_CASE							(    self   :			Dict)		->Mapping[str, Mapping[int, str]]:





           '''simple docstring'''

           if self.task == "multiple-choice":
                  A__   				=					{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
           else:
                  A__   				=					{0: '''batch''', 1: '''sequence'''}
           return OrderedDict(
               [
                   ('''input_ids''', dynamic_axis),
                   ('''attention_mask''', dynamic_axis),
                   ('''token_type_ids''', dynamic_axis),
               ])


