






'''simple docstring'''

from cva import destroyAllWindows, imread, imshow, waitKey







def    lowercase__			(				__UpperCamelCase   )->			Tuple:
      # getting number of pixels in the image
      UpperCamelCase  ,UpperCamelCase      = img.shape[0], img.shape[1]

      # converting each pixel's color to its negative
      for i in range(__UpperCamelCase   ):
            for j in range(__UpperCamelCase   ):
                  UpperCamelCase      = [255, 255, 255] - img[i][j]

      return img


if __name__ == "__main__":
    # read original image
    SCREAMING_SNAKE_CASE__     =       imread('image_data/lena.jpg', 1)

    # convert to its negative
    SCREAMING_SNAKE_CASE__     =       convert_to_negative(img)

    # show result image
    imshow('negative of original image', img)
    waitKey(0)
    destroyAllWindows()








'''simple docstring'''

import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE__     =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__     =       {'vocab_file': 'spm_char.model'}

SCREAMING_SNAKE_CASE__     =       {
    'vocab_file': {
        'microsoft/speecht5_asr': 'https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model',
        'microsoft/speecht5_tts': 'https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model',
        'microsoft/speecht5_vc': 'https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model',
    }
}

SCREAMING_SNAKE_CASE__     =       {
    'microsoft/speecht5_asr': 1_0_2_4,
    'microsoft/speecht5_tts': 1_0_2_4,
    'microsoft/speecht5_vc': 1_0_2_4,
}






class     a_						(      lowerCamelCase    ):
  lowercase							=				VOCAB_FILES_NAMES
  lowercase							=				PRETRAINED_VOCAB_FILES_MAP
  lowercase							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowercase							=				["""input_ids""", """attention_mask"""]

  def __init__(				self      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE="<s>"      ,		_SCREAMING_SNAKE_CASE="</s>"      ,		_SCREAMING_SNAKE_CASE="<unk>"      ,		_SCREAMING_SNAKE_CASE="<pad>"      ,		_SCREAMING_SNAKE_CASE = None      ,		**_SCREAMING_SNAKE_CASE      ,		)  ->				None:



        """simple docstring"""






        UpperCamelCase      = {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=_SCREAMING_SNAKE_CASE      ,		eos_token=_SCREAMING_SNAKE_CASE      ,		unk_token=_SCREAMING_SNAKE_CASE      ,		pad_token=_SCREAMING_SNAKE_CASE      ,		sp_model_kwargs=self.sp_model_kwargs      ,		**_SCREAMING_SNAKE_CASE      ,		)

        UpperCamelCase      = vocab_file

        UpperCamelCase      = spm.SentencePieceProcessor(**self.sp_model_kwargs				)
        self.sp_model.Load(_SCREAMING_SNAKE_CASE				)

  @property
  def   A__						(				self				)  ->				Tuple:



        """simple docstring"""






        return self.sp_model.get_piece_size()

  def   A__						(				self				)  ->				Tuple:



        """simple docstring"""






        UpperCamelCase      = {self.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE				): i for i in range(self.vocab_size				)}
        vocab.update(self.added_tokens_encoder				)
        return vocab

  def __getstate__(				self				)  ->				List[Any]:



        """simple docstring"""






        UpperCamelCase      = self.__dict__.copy()
        UpperCamelCase      = None
        return state

  def __setstate__(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				Union[str, Any]:



        """simple docstring"""






        UpperCamelCase      = d

        # for backward compatibility
        if not hasattr(self      ,		"""sp_model_kwargs"""				):
              UpperCamelCase      = {}

        UpperCamelCase      = spm.SentencePieceProcessor(**self.sp_model_kwargs				)
        self.sp_model.Load(self.vocab_file				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				List[str]:



        """simple docstring"""






        return self.sp_model.encode(_SCREAMING_SNAKE_CASE      ,		out_type=_SCREAMING_SNAKE_CASE				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				Tuple:



        """simple docstring"""






        return self.sp_model.piece_to_id(_SCREAMING_SNAKE_CASE				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				List[Any]:



        """simple docstring"""






        UpperCamelCase      = self.sp_model.IdToPiece(_SCREAMING_SNAKE_CASE				)
        return token

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				List[str]:



        """simple docstring"""






        UpperCamelCase      = []
        UpperCamelCase      = """"""
        for token in tokens:
              # make sure that special tokens are not decoded using sentencepiece model
              if token in self.all_special_tokens:
                    out_string += self.sp_model.decode(_SCREAMING_SNAKE_CASE				) + token
                    UpperCamelCase      = []
              else:
                    current_sub_tokens.append(_SCREAMING_SNAKE_CASE				)
        out_string += self.sp_model.decode(_SCREAMING_SNAKE_CASE				)
        return out_string.strip()

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE=None				)  ->				List[int]:



        """simple docstring"""






        if token_ids_a is None:
              return token_ids_a + [self.eos_token_id]
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return token_ids_a + token_ids_a + [self.eos_token_id]

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE = None      ,		_SCREAMING_SNAKE_CASE = False				)  ->				List[int]:



        """simple docstring"""






        if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=_SCREAMING_SNAKE_CASE      ,		token_ids_a=_SCREAMING_SNAKE_CASE      ,		already_has_special_tokens=_SCREAMING_SNAKE_CASE				)

        UpperCamelCase      = [1]
        if token_ids_a is None:
              return ([0] * len(_SCREAMING_SNAKE_CASE				)) + suffix_ones
        return ([0] * len(_SCREAMING_SNAKE_CASE				)) + ([0] * len(_SCREAMING_SNAKE_CASE				)) + suffix_ones


  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE = None				)  ->				Tuple[str]:



        """simple docstring"""






        if not os.path.isdir(_SCREAMING_SNAKE_CASE				):
              logger.error(F"Vocabulary path ({save_directory}) should be a directory"				)
              return
        UpperCamelCase      = os.path.join(
            _SCREAMING_SNAKE_CASE      ,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

        if os.path.abspath(self.vocab_file				) != os.path.abspath(_SCREAMING_SNAKE_CASE				) and os.path.isfile(self.vocab_file				):
              copyfile(self.vocab_file      ,		_SCREAMING_SNAKE_CASE				)
        elif not os.path.isfile(self.vocab_file				):
              with open(_SCREAMING_SNAKE_CASE      ,		"""wb"""				) as fi:
                    UpperCamelCase      = self.sp_model.serialized_model_proto()
                    fi.write(_SCREAMING_SNAKE_CASE				)

        return (out_vocab_file,)
