






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


__magic_name__:					Optional[Any]							=     logging.get_logger(__name__)

__magic_name__:					Optional[int]							=     {
    "artists_file": "artists.json",
    "lyrics_file": "lyrics.json",
    "genres_file": "genres.json",
}

__magic_name__:					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",
    },
}

__magic_name__:					Optional[int]							=     {
    "jukebox": 512,
}





class 	snake_case__ (							_lowerCAmelCase				):
	lowercase__						:					Any											=   VOCAB_FILES_NAMES
	lowercase__						:					Tuple											=   PRETRAINED_VOCAB_FILES_MAP
	lowercase__						:					Tuple											=   PRETRAINED_LYRIC_TOKENS_SIZES
	lowercase__						:					Tuple											=   ['''input_ids''', '''attention_mask''']
	def __init__(    self      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__=["v3", "v2", "v2"]      ,       lowerCAmelCase__=5_12      ,       lowerCAmelCase__=5      ,       lowerCAmelCase__="<|endoftext|>"      ,       **lowerCAmelCase__      ,       )							->				int:
							__magic_name__      :       Optional[Any]       						= AddedToken(lowerCAmelCase__      ,       lstrip=lowerCAmelCase__      ,       rstrip=lowerCAmelCase__			) if isinstance(lowerCAmelCase__      ,       lowerCAmelCase__			) else unk_token
							super().__init__(
							    unk_token=lowerCAmelCase__      ,       n_genres=lowerCAmelCase__      ,       version=lowerCAmelCase__      ,       max_n_lyric_tokens=lowerCAmelCase__      ,       **lowerCAmelCase__      ,       )
							__magic_name__      :       Tuple       						= version
							__magic_name__      :       List[Any]       						= max_n_lyric_tokens
							__magic_name__      :       List[str]       						= n_genres

							with open(lowerCAmelCase__      ,       encoding="""utf-8"""			) as vocab_handle:
													__magic_name__      :       Optional[Any]       						= json.load(lowerCAmelCase__			)

							with open(lowerCAmelCase__      ,       encoding="""utf-8"""			) as vocab_handle:
													__magic_name__      :       Optional[int]       						= json.load(lowerCAmelCase__			)

							with open(lowerCAmelCase__      ,       encoding="""utf-8"""			) as vocab_handle:
													__magic_name__      :       Dict       						= json.load(lowerCAmelCase__			)

							__magic_name__      :       Optional[int]       						= 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:
													__magic_name__      :       Tuple       						= oov.replace(R"""\-'"""      ,       R"""\-+'"""			)

							__magic_name__      :       Tuple       						= regex.compile(lowerCAmelCase__			)
							__magic_name__      :       List[Any]       						= {v: k for k, v in self.artists_encoder.items()}
							__magic_name__      :       Optional[Any]       						= {v: k for k, v in self.genres_encoder.items()}
							__magic_name__      :       List[str]       						= {v: k for k, v in self.lyrics_encoder.items()}
	@property
	def       __magic_name__    (    self			)							->				Tuple:
							return len(self.artists_encoder			) + len(self.genres_encoder			) + len(self.lyrics_encoder			)
	def       __magic_name__    (    self			)							->				Optional[int]:
							return dict(self.artists_encoder      ,       self.genres_encoder      ,       self.lyrics_encoder			)
	def       __magic_name__    (    self      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__			)							->				Any:
							__magic_name__      :       List[str]       						= [self.artists_encoder.get(lowerCAmelCase__      ,       0			) for artist in list_artists]
							for genres in range(len(lowerCAmelCase__			)			):
													__magic_name__      :       Tuple       						= [self.genres_encoder.get(lowerCAmelCase__      ,       0			) for genre in list_genres[genres]]
													__magic_name__      :       List[Any]       						= list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]			))

							__magic_name__      :       List[str]       						= [[self.lyrics_encoder.get(lowerCAmelCase__      ,       0			) for character in list_lyrics[0]], [], []]
							return artists_id, list_genres, lyric_ids
	def       __magic_name__    (    self      ,       lowerCAmelCase__			)							->				int:
							return list(lowerCAmelCase__			)
	def       __magic_name__    (    self      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       **lowerCAmelCase__			)							->				Dict:
							__magic_name__						,__magic_name__						,__magic_name__      :       Tuple       						= self.prepare_for_tokenization(lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__			)
							__magic_name__      :       Tuple       						= self._tokenize(lowerCAmelCase__			)
							return artist, genre, lyrics
	def       __magic_name__    (    self      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__ = False			)							->				Tuple[str, str, str, Dict[str, Any]]:
							for idx in range(len(self.version			)			):
													if self.version[idx] == "v3":
																			__magic_name__      :       List[Any]       						= artists[idx].lower()
																			__magic_name__      :       int       						= [genres[idx].lower()]
													else:
																			__magic_name__      :       List[str]       						= self._normalize(artists[idx]			) + """.v2"""
																			__magic_name__      :       List[Any]       						= [
																			    self._normalize(lowerCAmelCase__			) + """.v2""" for genre in genres[idx].split("""_"""			)
																			]  # split is for the full dictionary with combined genres

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

							__magic_name__      :       List[str]       						= self._run_strip_accents(lowerCAmelCase__			)
							__magic_name__      :       Any       						= lyrics.replace("""\\"""      ,       """\n"""			)
							__magic_name__      :       Tuple       						= self.out_of_vocab.sub(""""""      ,       lowerCAmelCase__			), [], []
							return artists, genres, lyrics
	def       __magic_name__    (    self      ,       lowerCAmelCase__			)							->				str:
							__magic_name__      :       Dict       						= unicodedata.normalize("""NFD"""      ,       lowerCAmelCase__			)
							__magic_name__      :       Union[str, Any]       						= []
							for char in text:
													__magic_name__      :       Any       						= unicodedata.category(lowerCAmelCase__			)
													if cat == "Mn":
																			continue
													output.append(lowerCAmelCase__			)
							return "".join(lowerCAmelCase__			)
	def       __magic_name__    (    self      ,       lowerCAmelCase__			)							->				str:
							__magic_name__      :       Optional[Any]       						= (
							    [chr(lowerCAmelCase__			) for i in range(ord("""a"""			)      ,       ord("""z"""			) + 1			)]
							    + [chr(lowerCAmelCase__			) for i in range(ord("""A"""			)      ,       ord("""Z"""			) + 1			)]
							    + [chr(lowerCAmelCase__			) for i in range(ord("""0"""			)      ,       ord("""9"""			) + 1			)]
							    + ["""."""]
							)
							__magic_name__      :       Tuple       						= frozenset(lowerCAmelCase__			)
							__magic_name__      :       Any       						= re.compile(R"""_+"""			)
							__magic_name__      :       str       						= """""".join([c if c in accepted else """_""" for c in text.lower()]			)
							__magic_name__      :       Union[str, Any]       						= pattern.sub("""_"""      ,       lowerCAmelCase__			).strip("""_"""			)
							return text
	def       __magic_name__    (    self      ,       lowerCAmelCase__			)							->				str:
							return " ".join(lowerCAmelCase__			)
	def       __magic_name__    (    self      ,       lowerCAmelCase__      ,       lowerCAmelCase__ = None      ,       lowerCAmelCase__ = False			)							->				Tuple:
							# Convert to TensorType
							if not isinstance(lowerCAmelCase__      ,       lowerCAmelCase__			):
													__magic_name__      :       List[str]       						= TensorType(lowerCAmelCase__			)

							# 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

													__magic_name__      :       Dict       						= tf.constant
													__magic_name__      :       Optional[Any]       						= 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

													__magic_name__      :       str       						= torch.tensor
													__magic_name__      :       Union[str, Any]       						= 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

													__magic_name__      :       List[str]       						= jnp.array
													__magic_name__      :       Any       						= _is_jax
							else:
													__magic_name__      :       Any       						= np.asarray
													__magic_name__      :       List[Any]       						= _is_numpy

							# Do the tensor conversion in batch

							try:
													if prepend_batch_axis:
																			__magic_name__      :       str       						= [inputs]

													if not is_tensor(lowerCAmelCase__			):
																			__magic_name__      :       str       						= as_tensor(lowerCAmelCase__			)
							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      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__=""      ,       lowerCAmelCase__="pt"			)							->				BatchEncoding:
							__magic_name__      :       str       						= [0, 0, 0]
							__magic_name__      :       List[Any]       						= [artist] * len(self.version			)
							__magic_name__      :       Union[str, Any]       						= [genres] * len(self.version			)

							__magic_name__						,__magic_name__						,__magic_name__      :       List[str]       						= self.tokenize(lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__			)
							__magic_name__						,__magic_name__						,__magic_name__      :       Tuple       						= self._convert_token_to_id(lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__			)

							__magic_name__      :       Optional[int]       						= [-INFINITY] * len(full_tokens[-1]			)
							__magic_name__      :       Union[str, Any]       						= [
							    self.convert_to_tensors(
							        [input_ids + [artists_id[i]] + genres_ids[i] + full_tokens[i]]      ,       tensor_type=lowerCAmelCase__			)
							    for i in range(len(self.version			)			)
							]
							return BatchEncoding({"""input_ids""": input_ids, """attention_masks""": attention_masks}			)
	def       __magic_name__    (    self      ,       lowerCAmelCase__      ,       lowerCAmelCase__ = None			)							->				Tuple[str]:
							if not os.path.isdir(lowerCAmelCase__			):
													logger.error(F'Vocabulary path ({save_directory}) should be a directory'			)
													return

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

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

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

							return (artists_file, genres_file, lyrics_file)







	def       __magic_name__    (    self      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__			)							->				Any:
							__magic_name__      :       Optional[Any]       						= self.artists_decoder.get(lowerCAmelCase__			)
							__magic_name__      :       str       						= [self.genres_decoder.get(lowerCAmelCase__			) for genre in genres_index]
							__magic_name__      :       Union[str, Any]       						= [self.lyrics_decoder.get(lowerCAmelCase__			) for character in lyric_index]
							return artist, genres, lyrics








def    UpperCamelCase						(	_A = 1,   _A = 1000			):






						"""simple docstring"""







						__magic_name__      :       Optional[int]       						= 1
						__magic_name__      :       Dict       						= 0

						for divide_by_number in range(_A,   digit + 1			):
												__magic_name__      :       list[int]       						= []
												__magic_name__      :       Any       						= numerator
												for _ in range(1,   digit + 1			):
																		if now_divide in has_been_divided:
																								if longest_list_length < len(_A			):
																														__magic_name__      :       int       						= len(_A			)
																														__magic_name__      :       Dict       						= divide_by_number
																		else:
																								has_been_divided.append(_A			)
																								__magic_name__      :       Optional[int]       						= now_divide * 10 % divide_by_number

						return the_digit


# Tests
if __name__ == "__main__":
		import doctest

		doctest.testmod()
