
"""simple docstring"""

import colorsys

from PIL import Image  # type: ignore






def 							A						(    snake_case				:int    , snake_case				:Any    , snake_case				:List[str]		)				->     float:
 __UpperCamelCase      =	x
 __UpperCamelCase      =	y
 for step in range(_lowerCamelCase		):  # noqa: B007
  __UpperCamelCase      =	a * a - b * b + x
  __UpperCamelCase      =	2 * a * b + y
  __UpperCamelCase      =	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						(    snake_case				:List[str]		)				->     tuple:


 if distance == 1:
  return (0, 0, 0)
 else:
  return (2_5_5, 2_5_5, 2_5_5)






def 							A						(    snake_case				:int		)				->     tuple:


 if distance == 1:
  return (0, 0, 0)
 else:
  return tuple(round(i * 2_5_5		) for i in colorsys.hsv_to_rgb(_lowerCamelCase    , 1    , 1		)		)






def 							A						(    snake_case				:Union[str, Any] = 8_0_0    , snake_case				:Dict = 6_0_0    , snake_case				:List[str] = -0.6    , snake_case				:Any = 0    , snake_case				:List[Any] = 3.2    , snake_case				:Union[str, Any] = 5_0    , snake_case				:Any = True    , )				->     Image.Image:
 __UpperCamelCase      =	Image.new('RGB'    , (image_width, image_height)		)
 __UpperCamelCase      =	img.load()

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

   __UpperCamelCase      =	get_distance(_lowerCamelCase    , _lowerCamelCase    , _lowerCamelCase		)

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

 return img


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       # colored version, full figure
       UpperCamelCase     :    Optional[int]       =			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 json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union

import numpy as np
import regex

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_flax_available, is_tf_available, is_torch_available, logging
from ...utils.generic import _is_jax, _is_numpy


UpperCamelCase     :    Tuple       =			logging.get_logger(__name__)

UpperCamelCase     :    int       =			{
    "artists_file": "artists.json",
    "lyrics_file": "lyrics.json",
    "genres_file": "genres.json",
}

UpperCamelCase     :    Optional[Any]       =			{
    "artists_file": {
        "jukebox": "https://huggingface.co/ArthurZ/jukebox/blob/main/artists.json",
    },
    "genres_file": {
        "jukebox": "https://huggingface.co/ArthurZ/jukebox/blob/main/genres.json",
    },
    "lyrics_file": {
        "jukebox": "https://huggingface.co/ArthurZ/jukebox/blob/main/lyrics.json",
    },
}

UpperCamelCase     :    Any       =			{
    "jukebox": 5_1_2,
}

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						VOCAB_FILES_NAMES
     lowercase						       =						PRETRAINED_VOCAB_FILES_MAP
     lowercase						       =						PRETRAINED_LYRIC_TOKENS_SIZES
     lowercase						       =						["input_ids", "attention_mask"]





     def __init__(     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase=["v3", "v2", "v2"]     ,					__UpperCAmelCase=512     ,					__UpperCAmelCase=5     ,					__UpperCAmelCase="<|endoftext|>"     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      __UpperCamelCase      =	AddedToken(__UpperCAmelCase     ,					lstrip=__UpperCAmelCase     ,					rstrip=__UpperCAmelCase				) if isinstance(__UpperCAmelCase     ,					__UpperCAmelCase				) else unk_token
      super().__init__(
          unk_token=__UpperCAmelCase     ,					n_genres=__UpperCAmelCase     ,					version=__UpperCAmelCase     ,					max_n_lyric_tokens=__UpperCAmelCase     ,					**__UpperCAmelCase     ,					)
      __UpperCamelCase      =	version
      __UpperCamelCase      =	max_n_lyric_tokens
      __UpperCamelCase      =	n_genres

      with open(__UpperCAmelCase     ,					encoding='utf-8'				) as vocab_handle:
       __UpperCamelCase      =	json.load(__UpperCAmelCase				)

      with open(__UpperCAmelCase     ,					encoding='utf-8'				) as vocab_handle:
       __UpperCamelCase      =	json.load(__UpperCAmelCase				)

      with open(__UpperCAmelCase     ,					encoding='utf-8'				) as vocab_handle:
       __UpperCamelCase      =	json.load(__UpperCAmelCase				)

      __UpperCamelCase      =	R'[^A-Za-z0-9.,:;!?\-\'\"()\[\] \t\n]+'
      # In v2, we had a n_vocab=80 and in v3 we missed + and so n_vocab=79 of characters.
      if len(self.lyrics_encoder				) == 79:
       __UpperCamelCase      =	oov.replace(R'\-\''     ,					R'\-+\''				)

      __UpperCamelCase      =	regex.compile(__UpperCAmelCase				)
      __UpperCamelCase      =	{v: k for k, v in self.artists_encoder.items()}
      __UpperCamelCase      =	{v: k for k, v in self.genres_encoder.items()}
      __UpperCamelCase      =	{v: k for k, v in self.lyrics_encoder.items()}





     @property
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      return len(self.artists_encoder				) + len(self.genres_encoder				) + len(self.lyrics_encoder				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      return dict(self.artists_encoder     ,					self.genres_encoder     ,					self.lyrics_encoder				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	[self.artists_encoder.get(__UpperCAmelCase     ,					0				) for artist in list_artists]
      for genres in range(len(__UpperCAmelCase				)				):
       __UpperCamelCase      =	[self.genres_encoder.get(__UpperCAmelCase     ,					0				) for genre in list_genres[genres]]
       __UpperCamelCase      =	list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]				))

      __UpperCamelCase      =	[[self.lyrics_encoder.get(__UpperCAmelCase     ,					0				) for character in list_lyrics[0]], [], []]
      return artists_id, list_genres, lyric_ids





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      return list(__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					**__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase  ,     __UpperCamelCase  ,     __UpperCamelCase      =	self.prepare_for_tokenization(__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)
      __UpperCamelCase      =	self._tokenize(__UpperCAmelCase				)
      return artist, genre, lyrics





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase = False				):

      '''simple docstring'''




      for idx in range(len(self.version				)				):
       if self.version[idx] == "v3":
        __UpperCamelCase      =	artists[idx].lower()
        __UpperCamelCase      =	[genres[idx].lower()]
       else:
        __UpperCamelCase      =	self._normalize(artists[idx]				) + '.v2'
        __UpperCamelCase      =	[
            self._normalize(__UpperCAmelCase				) + '.v2' for genre in genres[idx].split('_'				)
        ]  # split is for the full dictionary with combined genres

      if self.version[0] == "v2":
       __UpperCamelCase      =	regex.compile(R'[^A-Za-z0-9.,:;!?\-\'\"()\[\] \t\n]+'				)
       __UpperCamelCase      =	'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789.,:;!?-+\'\"()[] \t\n'
       __UpperCamelCase      =	{vocab[index]: index + 1 for index in range(len(__UpperCAmelCase				)				)}
       __UpperCamelCase      =	0
       __UpperCamelCase      =	len(__UpperCAmelCase				) + 1
       __UpperCamelCase      =	self.vocab
       __UpperCamelCase      =	{v: k for k, v in self.vocab.items()}
       __UpperCamelCase      =	''
      else:
       __UpperCamelCase      =	regex.compile(R'[^A-Za-z0-9.,:;!?\-+\'\"()\[\] \t\n]+'				)

      __UpperCamelCase      =	self._run_strip_accents(__UpperCAmelCase				)
      __UpperCamelCase      =	lyrics.replace('\\'     ,					'\n'				)
      __UpperCamelCase      =	self.out_of_vocab.sub(''     ,					__UpperCAmelCase				), [], []
      return artists, genres, lyrics





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	unicodedata.normalize('NFD'     ,					__UpperCAmelCase				)
      __UpperCamelCase      =	[]
      for char in text:
       __UpperCamelCase      =	unicodedata.category(__UpperCAmelCase				)
       if cat == "Mn":
        continue
       output.append(__UpperCAmelCase				)
      return "".join(__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	(
          [chr(__UpperCAmelCase				) for i in range(ord('a'				)     ,					ord('z'				) + 1				)]
          + [chr(__UpperCAmelCase				) for i in range(ord('A'				)     ,					ord('Z'				) + 1				)]
          + [chr(__UpperCAmelCase				) for i in range(ord('0'				)     ,					ord('9'				) + 1				)]
          + ['.']
      )
      __UpperCamelCase      =	frozenset(__UpperCAmelCase				)
      __UpperCamelCase      =	re.compile(R'_+'				)
      __UpperCamelCase      =	''.join([c if c in accepted else '_' for c in text.lower()]				)
      __UpperCamelCase      =	pattern.sub('_'     ,					__UpperCAmelCase				).strip('_'				)
      return text





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      return " ".join(__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None     ,					__UpperCAmelCase = False				):

      '''simple docstring'''




      if not isinstance(__UpperCAmelCase     ,					__UpperCAmelCase				):
       __UpperCamelCase      =	TensorType(__UpperCAmelCase				)

      # Get a function reference for the correct framework
      if tensor_type == TensorType.TENSORFLOW:
       if not is_tf_available():
        raise ImportError(
            'Unable to convert output to TensorFlow tensors format, TensorFlow is not installed.'				)
       import tensorflow as tf

       __UpperCamelCase      =	tf.constant
       __UpperCamelCase      =	tf.is_tensor
      elif tensor_type == TensorType.PYTORCH:
       if not is_torch_available():
        raise ImportError('Unable to convert output to PyTorch tensors format, PyTorch is not installed.'				)
       import torch

       __UpperCamelCase      =	torch.tensor
       __UpperCamelCase      =	torch.is_tensor
      elif tensor_type == TensorType.JAX:
       if not is_flax_available():
        raise ImportError('Unable to convert output to JAX tensors format, JAX is not installed.'				)
       import jax.numpy as jnp  # noqa: F811

       __UpperCamelCase      =	jnp.array
       __UpperCamelCase      =	_is_jax
      else:
       __UpperCamelCase      =	np.asarray
       __UpperCamelCase      =	_is_numpy

      # Do the tensor conversion in batch

      try:
       if prepend_batch_axis:
        __UpperCamelCase      =	[inputs]

       if not is_tensor(__UpperCAmelCase				):
        __UpperCamelCase      =	as_tensor(__UpperCAmelCase				)
      except:  # noqa E722
       raise ValueError(
           'Unable to create tensor, you should probably activate truncation and/or padding '
           'with \'padding=True\' \'truncation=True\' to have batched tensors with the same length.'				)

      return inputs





     def __call__(     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase=""     ,					__UpperCAmelCase="pt"				):

      '''simple docstring'''




      __UpperCamelCase      =	[0, 0, 0]
      __UpperCamelCase      =	[artist] * len(self.version				)
      __UpperCamelCase      =	[genres] * len(self.version				)

      __UpperCamelCase  ,     __UpperCamelCase  ,     __UpperCamelCase      =	self.tokenize(__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)
      __UpperCamelCase  ,     __UpperCamelCase  ,     __UpperCamelCase      =	self._convert_token_to_id(__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)

      __UpperCamelCase      =	[-INFINITY] * len(full_tokens[-1]				)
      __UpperCamelCase      =	[
          self.convert_to_tensors(
              [input_ids + [artists_id[i]] + genres_ids[i] + full_tokens[i]]     ,					tensor_type=__UpperCAmelCase				)
          for i in range(len(self.version				)				)
      ]
      return BatchEncoding({'input_ids': input_ids, 'attention_masks': attention_masks}				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




      if not os.path.isdir(__UpperCAmelCase				):
       logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
       return

      __UpperCamelCase      =	os.path.join(
          __UpperCAmelCase     ,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['artists_file']				)
      with open(__UpperCAmelCase     ,					'w'     ,					encoding='utf-8'				) as f:
       f.write(json.dumps(self.artists_encoder     ,					ensure_ascii=__UpperCAmelCase				)				)

      __UpperCamelCase      =	os.path.join(
          __UpperCAmelCase     ,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['genres_file']				)
      with open(__UpperCAmelCase     ,					'w'     ,					encoding='utf-8'				) as f:
       f.write(json.dumps(self.genres_encoder     ,					ensure_ascii=__UpperCAmelCase				)				)

      __UpperCamelCase      =	os.path.join(
          __UpperCAmelCase     ,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['lyrics_file']				)
      with open(__UpperCAmelCase     ,					'w'     ,					encoding='utf-8'				) as f:
       f.write(json.dumps(self.lyrics_encoder     ,					ensure_ascii=__UpperCAmelCase				)				)

      return (artists_file, genres_file, lyrics_file)







     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	self.artists_decoder.get(__UpperCAmelCase				)
      __UpperCamelCase      =	[self.genres_decoder.get(__UpperCAmelCase				) for genre in genres_index]
      __UpperCamelCase      =	[self.lyrics_decoder.get(__UpperCAmelCase				) for character in lyric_index]
      return artist, genres, lyrics



