






"""simple docstring"""





from typing import List, Optional, Union

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






class      a						(					_UpperCAmelCase		):
    SCREAMING_SNAKE_CASE						:     List[Any]						= ['image_processor', 'tokenizer']
    SCREAMING_SNAKE_CASE						:     Union[str, Any]						= 'BridgeTowerImageProcessor'
    SCREAMING_SNAKE_CASE						:     int						= ('RobertaTokenizer', 'RobertaTokenizerFast')






    def __init__(       self     :							int       ,						__SCREAMING_SNAKE_CASE     :							int       ,						__SCREAMING_SNAKE_CASE     :							int					)     ->		str:
      super().__init__(SCREAMING_SNAKE_CASE_       ,						SCREAMING_SNAKE_CASE_					)






    def __call__(       self     :							Optional[Any]       ,						__SCREAMING_SNAKE_CASE     :							Optional[int]       ,						__SCREAMING_SNAKE_CASE     :							Any = None       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any] = True       ,						__SCREAMING_SNAKE_CASE     :							str = False       ,						__SCREAMING_SNAKE_CASE     :							Tuple = None       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any] = None       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any] = 0       ,						__SCREAMING_SNAKE_CASE     :							Optional[int] = None       ,						__SCREAMING_SNAKE_CASE     :							Tuple = None       ,						__SCREAMING_SNAKE_CASE     :							Tuple = None       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any] = False       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any] = False       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any] = False       ,						__SCREAMING_SNAKE_CASE     :							List[Any] = False       ,						__SCREAMING_SNAKE_CASE     :							Optional[int] = True       ,						__SCREAMING_SNAKE_CASE     :							str = None       ,						**__SCREAMING_SNAKE_CASE     :							List[Any]       ,						)     ->		BatchEncoding:
      lowerCamelCase_         =						self.tokenizer(
          text=SCREAMING_SNAKE_CASE_       ,						add_special_tokens=SCREAMING_SNAKE_CASE_       ,						padding=SCREAMING_SNAKE_CASE_       ,						truncation=SCREAMING_SNAKE_CASE_       ,						max_length=SCREAMING_SNAKE_CASE_       ,						stride=SCREAMING_SNAKE_CASE_       ,						pad_to_multiple_of=SCREAMING_SNAKE_CASE_       ,						return_token_type_ids=SCREAMING_SNAKE_CASE_       ,						return_attention_mask=SCREAMING_SNAKE_CASE_       ,						return_overflowing_tokens=SCREAMING_SNAKE_CASE_       ,						return_special_tokens_mask=SCREAMING_SNAKE_CASE_       ,						return_offsets_mapping=SCREAMING_SNAKE_CASE_       ,						return_length=SCREAMING_SNAKE_CASE_       ,						verbose=SCREAMING_SNAKE_CASE_       ,						return_tensors=SCREAMING_SNAKE_CASE_       ,						**SCREAMING_SNAKE_CASE_       ,						)
      # add pixel_values + pixel_mask
      lowerCamelCase_         =						self.image_processor(
          SCREAMING_SNAKE_CASE_       ,						return_tensors=SCREAMING_SNAKE_CASE_       ,						do_normalize=SCREAMING_SNAKE_CASE_       ,						do_center_crop=SCREAMING_SNAKE_CASE_       ,						**SCREAMING_SNAKE_CASE_					)
      encoding.update(SCREAMING_SNAKE_CASE_					)

      return encoding






    def    UpperCamelCase       (       self     :							Optional[int]       ,						*__SCREAMING_SNAKE_CASE     :							Optional[int]       ,						**__SCREAMING_SNAKE_CASE     :							Union[str, Any]					)     ->		Optional[Any]:
      return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE_       ,						**SCREAMING_SNAKE_CASE_					)






    def    UpperCamelCase       (       self     :							Any       ,						*__SCREAMING_SNAKE_CASE     :							str       ,						**__SCREAMING_SNAKE_CASE     :							List[str]					)     ->		List[Any]:
      return self.tokenizer.decode(*SCREAMING_SNAKE_CASE_       ,						**SCREAMING_SNAKE_CASE_					)






    @property
    def    UpperCamelCase       (       self     :							Optional[int]					)     ->		Any:
      lowerCamelCase_         =						self.tokenizer.model_input_names
      lowerCamelCase_         =						self.image_processor.model_input_names
      return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names					)					)








'''simple docstring'''



from numpy import exp, pi, sqrt



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				Optional[int]      ,    UpperCAmelCase_    :				float = 0.0      ,    UpperCAmelCase_    :				float = 1.0							)     ->		int:
     return 1 / sqrt(2 * pi * sigma**2							) * exp(-((x - mu) ** 2) / (2 * sigma**2)							)


if __name__ == "__main__":
      import doctest

      doctest.testmod()






