

'''simple docstring'''






import colorsys

from PIL import Image  # type: ignore


def 		_A     (    A__     ,				A__     ,				A__      ):






 """simple docstring"""



 __lowercase							  = x
 __lowercase							  = y
 for step in range(A__      ):  # noqa: B007
  __lowercase							  = a * a - b * b + x
  __lowercase							  = 2 * a * b + y
  __lowercase							  = a_new

  # divergence happens for all complex number with an absolute value
  # greater than 4
  if a * a + b * b > 4:
   break
 return step / (max_step - 1)


def 		_A     (    A__      ):






 """simple docstring"""



 if distance == 1:
  return (0, 0, 0)
 else:
  return (255, 255, 255)


def 		_A     (    A__      ):






 """simple docstring"""



 if distance == 1:
  return (0, 0, 0)
 else:
  return tuple(round(i * 255      ) for i in colorsys.hsv_to_rgb(A__     ,				1     ,				1      )      )


def 		_A     (    A__ = 800     ,				A__ = 600     ,				A__ = -0.6     ,				A__ = 0     ,				A__ = 3.2     ,				A__ = 50     ,				A__ = True     ,				):






 """simple docstring"""



 __lowercase							  = Image.new('''RGB'''     ,				(image_width, image_height)      )
 __lowercase							  = img.load()

 # loop through the image-coordinates
 for image_x in range(A__      ):
  for image_y in range(A__      ):
   # determine the figure-coordinates based on the image-coordinates
   __lowercase							  = figure_width / image_width * image_height
   __lowercase							  = figure_center_x + (image_x / image_width - 0.5) * figure_width
   __lowercase							  = figure_center_y + (image_y / image_height - 0.5) * figure_height

   __lowercase							  = get_distance(A__     ,				A__     ,				A__      )

   # color the corresponding pixel based on the selected coloring-function
   if use_distance_color_coding:
    __lowercase							  = get_color_coded_rgb(A__      )
   else:
    __lowercase							  = get_black_and_white_rgb(A__      )

 return img


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 # colored version, full figure
 lowerCAmelCase__											=	get_image()

 # uncomment for colored version, different section, zoomed in
 # img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
 # figure_width = 0.8)

 # uncomment for black and white version, full figure
 # img = get_image(use_distance_color_coding = False)

 # uncomment to save the image
 # img.save("mandelbrot.png")

 img.show()




'''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


lowerCAmelCase__											=	logging.get_logger(__name__)

lowerCAmelCase__											=	{'''vocab_file''': '''spiece.model'''}

lowerCAmelCase__											=	{
    '''vocab_file''': {
        '''bert_for_seq_generation''': (
            '''https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model'''
        ),
    }
}

lowerCAmelCase__											=	{'''bert_for_seq_generation''': 512}






class 			lowercase_	(lowerCamelCase__      ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE    :  List[Any]							=			VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE    :  Dict							=			PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE    :  Optional[int]							=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE    :  List[int]							=			[]
  SCREAMING_SNAKE_CASE    :  Any							=			['input_ids', 'attention_mask']






  def __init__(      self   :     Optional[Any]					,lowercase__   :     Tuple					,lowercase__   :     Tuple="<s>"					,lowercase__   :     Union[str, Any]="</s>"					,lowercase__   :     str="<unk>"					,lowercase__   :     Tuple="<pad>"					,lowercase__   :     Union[str, Any]="<::::>"					,lowercase__   :     Optional[Dict[str, Any]] = None					,**lowercase__   :     Any					,):
   __lowercase							  = {} if sp_model_kwargs is None else sp_model_kwargs

   # Add extra_ids to the special token list
   super().__init__(
       bos_token=lowercase__					,eos_token=lowercase__					,unk_token=lowercase__					,pad_token=lowercase__					,sep_token=lowercase__					,sp_model_kwargs=self.sp_model_kwargs					,**lowercase__					,)

   __lowercase							  = vocab_file

   __lowercase							  = spm.SentencePieceProcessor(**self.sp_model_kwargs			)
   self.sp_model.Load(lowercase__			)






  @property
  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]			):
   return self.sp_model.get_piece_size()






  def 					SCREAMING_SNAKE_CASE      (      self   :     Union[str, Any]			):
   __lowercase							  = {self.convert_ids_to_tokens(lowercase__			): i for i in range(self.vocab_size			)}
   vocab.update(self.added_tokens_encoder			)
   return vocab






  def __getstate__(      self   :     str			):
   __lowercase							  = self.__dict__.copy()
   __lowercase							  = None
   return state






  def __setstate__(      self   :     Optional[int]					,lowercase__   :     Optional[Any]			):
   __lowercase							  = d

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

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






  def 					SCREAMING_SNAKE_CASE      (      self   :     str					,lowercase__   :     str			):
   return self.sp_model.encode(lowercase__					,out_type=lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Tuple					,lowercase__   :     Union[str, Any]			):
   return self.sp_model.piece_to_id(lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Any					,lowercase__   :     Tuple			):
   __lowercase							  = self.sp_model.IdToPiece(lowercase__			)
   return token






  def 					SCREAMING_SNAKE_CASE      (      self   :     Optional[int]					,lowercase__   :     int			):
   __lowercase							  = []
   __lowercase							  = ''''''
   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(lowercase__			) + token
     __lowercase							  = []
    else:
     current_sub_tokens.append(lowercase__			)
   out_string += self.sp_model.decode(lowercase__			)
   return out_string.strip()






  def 					SCREAMING_SNAKE_CASE      (      self   :     int					,lowercase__   :     str					,lowercase__   :     Optional[str] = None			):
   if not os.path.isdir(lowercase__			):
    logger.error(F"Vocabulary path ({save_directory}) should be a directory"			)
    return
   __lowercase							  = os.path.join(
       lowercase__					,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)

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

   return (out_vocab_file,)

