






import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

lowerCamelCase__       		=  logging.get_logger(__name__)


lowerCamelCase__       		=  {name: getattr(transformers, name + """Fast""") for name in SLOW_TO_FAST_CONVERTERS}






def 	UpperCamelCase	(							snake_case__  : Optional[Any]						,snake_case__  : Tuple						,snake_case__  : int						,snake_case__  : List[str]	):




     '''simple docstring'''






     if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
          raise ValueError(f'''Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys()	)}.'''	)

     if tokenizer_name is None:
          __snake_case      :Tuple 							=    TOKENIZER_CLASSES
     else:
          __snake_case      :Tuple 							=    {tokenizer_name: getattr(snake_case__						,tokenizer_name + """Fast"""	)}

     logger.info(f'''Loading tokenizer classes: {tokenizer_names}'''	)

     for tokenizer_name in tokenizer_names:
          __snake_case      :Optional[Any] 							=    TOKENIZER_CLASSES[tokenizer_name]

          __snake_case      :Union[str, Any] 							=    True
          if checkpoint_name is None:
               __snake_case      :Dict 							=    list(tokenizer_class.max_model_input_sizes.keys()	)
          else:
               __snake_case      :Optional[int] 							=    [checkpoint_name]

          logger.info(f'''For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}'''	)

          for checkpoint in checkpoint_names:
               logger.info(f'''Loading {tokenizer_class.__class__.__name__} {checkpoint}'''	)

               # Load tokenizer
               __snake_case      :Optional[Any] 							=    tokenizer_class.from_pretrained(snake_case__						,force_download=snake_case__	)

               # Save fast tokenizer
               logger.info(f'''Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}'''	)

               # For organization names we create sub-directories
               if "/" in checkpoint:
                    __snake_case							,			__snake_case      :Optional[int] 							=    checkpoint.split("""/"""	)
                    __snake_case      :Optional[int] 							=    os.path.join(snake_case__						,snake_case__	)
               elif add_prefix:
                    __snake_case      :Optional[int] 							=    checkpoint
                    __snake_case      :Dict 							=    dump_path
               else:
                    __snake_case      :str 							=    None
                    __snake_case      :str 							=    dump_path

               logger.info(f'''=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}'''	)

               if checkpoint in list(tokenizer.pretrained_vocab_files_map.values()	)[0]:
                    __snake_case      :Dict 							=    list(tokenizer.pretrained_vocab_files_map.values()	)[0][checkpoint]
                    __snake_case      :Optional[Any] 							=    file_path.split(snake_case__	)[-1][0]
                    if next_char == "/":
                         __snake_case      :Optional[int] 							=    os.path.join(snake_case__						,snake_case__	)
                         __snake_case      :Dict 							=    None

                    logger.info(f'''=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}'''	)

               __snake_case      :Union[str, Any] 							=    tokenizer.save_pretrained(
                   snake_case__						,legacy_format=snake_case__						,filename_prefix=snake_case__	)
               logger.info(f'''=> File names {file_names}'''	)

               for file_name in file_names:
                    if not file_name.endswith("""tokenizer.json"""	):
                         os.remove(snake_case__	)
                         logger.info(f'''=> removing {file_name}'''	)


if __name__ == "__main__":
     lowerCamelCase__       		=  argparse.ArgumentParser()
     # Required parameters
     parser.add_argument(
         """--dump_path""", default=None, type=str, required=True, help="""Path to output generated fast tokenizer files."""
     )
     parser.add_argument(
         """--tokenizer_name""",
         default=None,
         type=str,
         help=(
             f'''Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will '''
             """download and convert all the checkpoints from AWS."""
         ),
     )
     parser.add_argument(
         """--checkpoint_name""",
         default=None,
         type=str,
         help="""Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.""",
     )
     parser.add_argument(
         """--force_download""",
         action="""store_true""",
         help="""Re-download checkpoints.""",
     )
     lowerCamelCase__       		=  parser.parse_args()

     convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)










import colorsys

from PIL import Image  # type: ignore






def 	UpperCamelCase	(							snake_case__  : float						,snake_case__  : float						,snake_case__  : int	):




     '''simple docstring'''






     __snake_case      :List[Any] 							=    x
     __snake_case      :str 							=    y
     for step in range(snake_case__	):  # noqa: B007
          __snake_case      :Tuple 							=    a * a - b * b + x
          __snake_case      :Dict 							=    2 * a * b + y
          __snake_case      :str 							=    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 	UpperCamelCase	(							snake_case__  : float	):




     '''simple docstring'''






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






def 	UpperCamelCase	(							snake_case__  : float	):




     '''simple docstring'''






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






def 	UpperCamelCase	(							snake_case__  : int = 800						,snake_case__  : int = 600						,snake_case__  : float = -0.6						,snake_case__  : float = 0						,snake_case__  : float = 3.2						,snake_case__  : int = 50						,snake_case__  : bool = True						,):




     '''simple docstring'''






     __snake_case      :Tuple 							=    Image.new("""RGB"""						,(image_width, image_height)	)
     __snake_case      :Dict 							=    img.load()

     # loop through the image-coordinates
     for image_x in range(snake_case__	):
          for image_y in range(snake_case__	):
               # determine the figure-coordinates based on the image-coordinates
               __snake_case      :Dict 							=    figure_width / image_width * image_height
               __snake_case      :Any 							=    figure_center_x + (image_x / image_width - 0.5) * figure_width
               __snake_case      :List[str] 							=    figure_center_y + (image_y / image_height - 0.5) * figure_height

               __snake_case      :Tuple 							=    get_distance(snake_case__						,snake_case__						,snake_case__	)

               # color the corresponding pixel based on the selected coloring-function
               if use_distance_color_coding:
                    __snake_case      :Optional[int] 							=    get_color_coded_rgb(snake_case__	)
               else:
                    __snake_case      :Optional[int] 							=    get_black_and_white_rgb(snake_case__	)

     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()


