






import warnings
from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType


class 						_a       (  UpperCAmelCase__    ):






  """simple docstring"""





  A_						=   ["""image_processor""", """tokenizer"""]
  A_						=   """FlavaImageProcessor"""
  A_						=   ("""BertTokenizer""", """BertTokenizerFast""")




  def __init__(     self		,		_UpperCAmelCase=None		,		_UpperCAmelCase=None		,		**_UpperCAmelCase )			-> Union[str, Any]:
     UpperCamelCase_									=     None
     if "feature_extractor" in kwargs:
        warnings.warn(
            'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
            ' instead.'		,		_UpperCAmelCase		,		)
        UpperCamelCase_									=     kwargs.pop('feature_extractor' )

     UpperCamelCase_									=     image_processor if image_processor is not None else feature_extractor
     if image_processor is None:
        raise ValueError('You need to specify an `image_processor`.' )
     if tokenizer is None:
        raise ValueError('You need to specify a `tokenizer`.' )

     super().__init__(_UpperCAmelCase		,		_UpperCAmelCase )
     UpperCamelCase_									=     self.image_processor




  def __call__(     self		,		_UpperCAmelCase = None		,		_UpperCAmelCase = None		,		_UpperCAmelCase = True		,		_UpperCAmelCase = False		,		_UpperCAmelCase = False		,		_UpperCAmelCase = None		,		_UpperCAmelCase = 0		,		_UpperCAmelCase = None		,		_UpperCAmelCase = None		,		_UpperCAmelCase = None		,		_UpperCAmelCase = None		,		_UpperCAmelCase = None		,		_UpperCAmelCase = False		,		_UpperCAmelCase = False		,		_UpperCAmelCase = False		,		_UpperCAmelCase = False		,		_UpperCAmelCase = True		,		_UpperCAmelCase = None		,		**_UpperCAmelCase		,		)			-> List[str]:

     if text is None and images is None:
        raise ValueError('You have to specify either text or images. Both cannot be none.' )

     if text is not None:
        UpperCamelCase_									=     self.tokenizer(
            text=_UpperCAmelCase		,		add_special_tokens=_UpperCAmelCase		,		padding=_UpperCAmelCase		,		truncation=_UpperCAmelCase		,		max_length=_UpperCAmelCase		,		stride=_UpperCAmelCase		,		pad_to_multiple_of=_UpperCAmelCase		,		return_token_type_ids=_UpperCAmelCase		,		return_attention_mask=_UpperCAmelCase		,		return_overflowing_tokens=_UpperCAmelCase		,		return_special_tokens_mask=_UpperCAmelCase		,		return_offsets_mapping=_UpperCAmelCase		,		return_length=_UpperCAmelCase		,		verbose=_UpperCAmelCase		,		return_tensors=_UpperCAmelCase		,		**_UpperCAmelCase		,		)
     if images is not None:
        UpperCamelCase_									=     self.image_processor(
            _UpperCAmelCase		,		return_image_mask=_UpperCAmelCase		,		return_codebook_pixels=_UpperCAmelCase		,		return_tensors=_UpperCAmelCase		,		**_UpperCAmelCase		,		)

     if text is not None and images is not None:
        encoding.update(_UpperCAmelCase )
        return encoding
     elif text is not None:
        return encoding
     else:
        return BatchEncoding(data=dict(**_UpperCAmelCase )		,		tensor_type=_UpperCAmelCase )




  def    _UpperCAmelCase     (     self		,		*_UpperCAmelCase		,		**_UpperCAmelCase )			-> List[str]:
     return self.tokenizer.batch_decode(*_UpperCAmelCase		,		**_UpperCAmelCase )




  def    _UpperCAmelCase     (     self		,		*_UpperCAmelCase		,		**_UpperCAmelCase )			-> List[str]:
     return self.tokenizer.decode(*_UpperCAmelCase		,		**_UpperCAmelCase )




  @property
  def    _UpperCAmelCase     (     self )			-> List[str]:
     UpperCamelCase_									=     self.tokenizer.model_input_names
     UpperCamelCase_									=     self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )




  @property
  def    _UpperCAmelCase     (     self )			-> str:
     warnings.warn(
         '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'		,		_UpperCAmelCase		,		)
     return self.image_processor_class




  @property
  def    _UpperCAmelCase     (     self )			-> Dict:
     warnings.warn(
         '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'		,		_UpperCAmelCase		,		)
     return self.image_processor













import os
from math import logaa






def     _snake_case    (__lowercase = "base_exp.txt"):
   UpperCamelCase_									=     0
   UpperCamelCase_									=     0
   for i, line in enumerate(open(os.path.join(os.path.dirname(__lowercase)    ,      __lowercase))):
      UpperCamelCase_		,      UpperCamelCase_									=     list(map(__lowercase    ,      line.split(',')))
      if x * logaa(__lowercase) > largest:
         UpperCamelCase_									=     x * logaa(__lowercase)
         UpperCamelCase_									=     i + 1
   return result


if __name__ == "__main__":
 print(solution())





