
from __future__ import annotations



def 		lowercase_     (  A__					,						A__						)				->				Union[str, Any]:
    """simple docstring"""

    snake_case	,				snake_case						=   0, len(UpperCAmelCase_						) - 1
    while start_ind <= end_ind:
        if array[start_ind] == search_item:
            return start_ind
        elif array[end_ind] == search_item:
            return end_ind
        else:
            start_ind += 1
            end_ind -= 1
    # returns -1 if search_item is not found in array
    return -1


if __name__ == "__main__":
   print(double_linear_search(list(range(1_00)), 40))




"""simple docstring"""



import os

from ...utils import logging
from .utils import DataProcessor, InputExample


SCREAMING_SNAKE_CASE_       :						Dict					=    logging.get_logger(__name__)



class        a    (							_lowerCamelCase					):



    """simple docstring"""



    def __init__(  self:			Tuple     ,    UpperCamelCase:			Optional[Any]     ,    UpperCamelCase:			Optional[int]=None							):






         """simple docstring"""


         A__				      =	language
         A__				      =	train_language

    def 					UpperCamelCase						(  self:			Union[str, Any]     ,    UpperCamelCase:			str							):






         """simple docstring"""


         A__				      =	self.language if self.train_language is None else self.train_language
         A__				      =	self._read_tsv(os.path.join(UpperCamelCase     ,    f"""XNLI-MT-1.0/multinli/multinli.train.{lg}.tsv"""							)							)
         A__				      =	[]
         for i, line in enumerate(UpperCamelCase							):
              if i == 0:
                   continue
              A__				      =	f"""train-{i}"""
              A__				      =	line[0]
              A__				      =	line[1]
              A__				      =	"""contradiction""" if line[2] == """contradictory""" else line[2]
              if not isinstance(UpperCamelCase     ,    UpperCamelCase							):
                   raise ValueError(f"""Training input {text_a} is not a string"""							)
              if not isinstance(UpperCamelCase     ,    UpperCamelCase							):
                   raise ValueError(f"""Training input {text_b} is not a string"""							)
              if not isinstance(UpperCamelCase     ,    UpperCamelCase							):
                   raise ValueError(f"""Training label {label} is not a string"""							)
              examples.append(InputExample(guid=UpperCamelCase     ,    text_a=UpperCamelCase     ,    text_b=UpperCamelCase     ,    label=UpperCamelCase							)							)
         return examples

    def 					UpperCamelCase						(  self:			Dict     ,    UpperCamelCase:			Union[str, Any]							):






         """simple docstring"""


         A__				      =	self._read_tsv(os.path.join(UpperCamelCase     ,    """XNLI-1.0/xnli.test.tsv"""							)							)
         A__				      =	[]
         for i, line in enumerate(UpperCamelCase							):
              if i == 0:
                   continue
              A__				      =	line[0]
              if language != self.language:
                   continue
              A__				      =	f"""test-{i}"""
              A__				      =	line[6]
              A__				      =	line[7]
              A__				      =	line[1]
              if not isinstance(UpperCamelCase     ,    UpperCamelCase							):
                   raise ValueError(f"""Training input {text_a} is not a string"""							)
              if not isinstance(UpperCamelCase     ,    UpperCamelCase							):
                   raise ValueError(f"""Training input {text_b} is not a string"""							)
              if not isinstance(UpperCamelCase     ,    UpperCamelCase							):
                   raise ValueError(f"""Training label {label} is not a string"""							)
              examples.append(InputExample(guid=UpperCamelCase     ,    text_a=UpperCamelCase     ,    text_b=UpperCamelCase     ,    label=UpperCamelCase							)							)
         return examples





    def 					UpperCamelCase						(  self:			Tuple							):






         """simple docstring"""


         return ["contradiction", "entailment", "neutral"]

SCREAMING_SNAKE_CASE_       :						int					=    {
    'xnli': XnliProcessor,
}

SCREAMING_SNAKE_CASE_       :						List[Any]					=    {
    'xnli': 'classification',
}

SCREAMING_SNAKE_CASE_       :						str					=    {
    'xnli': 3,
}






