
'''simple docstring'''

import os

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


_UpperCAmelCase   :      int 						=  logging.get_logger(__name__)

class 			UpperCAmelCase				(					a_ ):





		"""simple docstring"""





		def __init__(    self  ,					_snake_case  ,					_snake_case=None     )				->    Optional[int]:
				_UpperCamelCase       : Dict    =      language
				_UpperCamelCase       : Union[str, Any]    =      train_language
		def _lowercase  (    self  ,					_snake_case     )				->    Dict:
				_UpperCamelCase       : str    =      self.language if self.train_language is None else self.train_language
				_UpperCamelCase       : Union[str, Any]    =      self._read_tsv(os.path.join(_snake_case  ,					F'''XNLI-MT-1.0/multinli/multinli.train.{lg}.tsv'''     )     )
				_UpperCamelCase       : str    =      []
				for i, line in enumerate(_snake_case     ):
						if i == 0:
								continue
						_UpperCamelCase       : Optional[Any]    =      F'''train-{i}'''
						_UpperCamelCase       : Dict    =      line[0]
						_UpperCamelCase       : Any    =      line[1]
						_UpperCamelCase       : Union[str, Any]    =      '''contradiction''' if line[2] == '''contradictory''' else line[2]
						if not isinstance(_snake_case  ,					_snake_case     ):
								raise ValueError(F'''Training input {text_a} is not a string'''     )
						if not isinstance(_snake_case  ,					_snake_case     ):
								raise ValueError(F'''Training input {text_b} is not a string'''     )
						if not isinstance(_snake_case  ,					_snake_case     ):
								raise ValueError(F'''Training label {label} is not a string'''     )
						examples.append(InputExample(guid=_snake_case  ,					text_a=_snake_case  ,					text_b=_snake_case  ,					label=_snake_case     )     )
				return examples
		def _lowercase  (    self  ,					_snake_case     )				->    Any:
				_UpperCamelCase       : Dict    =      self._read_tsv(os.path.join(_snake_case  ,					'''XNLI-1.0/xnli.test.tsv'''     )     )
				_UpperCamelCase       : Dict    =      []
				for i, line in enumerate(_snake_case     ):
						if i == 0:
								continue
						_UpperCamelCase       : List[Any]    =      line[0]
						if language != self.language:
								continue
						_UpperCamelCase       : Optional[Any]    =      F'''test-{i}'''
						_UpperCamelCase       : Tuple    =      line[6]
						_UpperCamelCase       : Union[str, Any]    =      line[7]
						_UpperCamelCase       : Dict    =      line[1]
						if not isinstance(_snake_case  ,					_snake_case     ):
								raise ValueError(F'''Training input {text_a} is not a string'''     )
						if not isinstance(_snake_case  ,					_snake_case     ):
								raise ValueError(F'''Training input {text_b} is not a string'''     )
						if not isinstance(_snake_case  ,					_snake_case     ):
								raise ValueError(F'''Training label {label} is not a string'''     )
						examples.append(InputExample(guid=_snake_case  ,					text_a=_snake_case  ,					text_b=_snake_case  ,					label=_snake_case     )     )
				return examples




		def _lowercase  (    self     )				->    Tuple:
				return ["contradiction", "entailment", "neutral"]







_UpperCAmelCase   :      Optional[Any] 						=  {
    """xnli""": XnliProcessor,
}

_UpperCAmelCase   :      List[Any] 						=  {
    """xnli""": """classification""",
}

_UpperCAmelCase   :      Tuple 						=  {
    """xnli""": 3,
}







'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


_UpperCAmelCase   :      Optional[int] 						=  logging.get_logger(__name__)

class 			UpperCAmelCase				(					a_ ):





		"""simple docstring"""





		def __init__(    self  ,					*_snake_case  ,					**_snake_case     )				->    None:
				warnings.warn(
				    '''The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
				    ''' Please use MobileNetV2ImageProcessor instead.'''  ,					_snake_case  ,					)
				super().__init__(*_snake_case  ,					**_snake_case     )





