




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


lowerCamelCase    :		Optional[int]			   =							logging.get_logger(__name__)

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

lowerCamelCase    :		str			   =							{
    "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",
    },
}

lowerCamelCase    :		str			   =							{
    "jukebox": 512,
}







class   A(						UpperCamelCase       ):



 '''simple docstring'''


 UpperCamelCase						       =						VOCAB_FILES_NAMES
 UpperCamelCase						       =						PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase						       =						PRETRAINED_LYRIC_TOKENS_SIZES
 UpperCamelCase						       =						['''input_ids''', '''attention_mask''']

 def __init__(    self :  Dict						,							A_ :  Optional[Any]						,							A_ :  Any						,							A_ :  int						,							A_ :  Dict=["v3", "v2", "v2"]						,							A_ :  str=512						,							A_ :  Optional[Any]=5						,							A_ :  int="<|endoftext|>"						,							**A_ :  Any						,							)       ->     List[Any]:

       """simple docstring"""






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

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

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

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

       lowerCamelCase_							=   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:
             lowerCamelCase_							=   oov.replace(r'\-\''						,							r'\-+\''  )

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

 @property
 def     a__			(    self :  Tuple  )       ->     List[Any]:

       """simple docstring"""






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

 def     a__			(    self :  int  )       ->     Dict:

       """simple docstring"""






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

 def     a__			(    self :  List[str]						,							A_ :  Tuple						,							A_ :  Tuple						,							A_ :  Tuple  )       ->     Optional[Any]:

       """simple docstring"""






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

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

 def     a__			(    self :  Union[str, Any]						,							A_ :  str  )       ->     Any:

       """simple docstring"""






       return list(A_  )

 def     a__			(    self :  Union[str, Any]						,							A_ :  Any						,							A_ :  Union[str, Any]						,							A_ :  List[str]						,							**A_ :  Optional[int]  )       ->     int:

       """simple docstring"""






       lowerCamelCase_					,    lowerCamelCase_					,    lowerCamelCase_							=   self.prepare_for_tokenization(A_						,							A_						,							A_  )
       lowerCamelCase_							=   self._tokenize(A_  )
       return artist, genre, lyrics

 def     a__			(    self :  str						,							A_ :  str						,							A_ :  str						,							A_ :  str						,							A_ :  bool = False  )       ->     Tuple[str, str, str, Dict[str, Any]]:

       """simple docstring"""






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

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

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

 def     a__			(    self :  List[Any]						,							A_ :  Union[str, Any]  )       ->     Tuple:

       """simple docstring"""






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

 def     a__			(    self :  Any						,							A_ :  str  )       ->     str:

       """simple docstring"""






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

 def     a__			(    self :  Any						,							A_ :  List[str]  )       ->     str:

       """simple docstring"""






       return " ".join(A_  )

 def     a__			(    self :  List[str]						,							A_ :  Optional[int]						,							A_ :  Optional[Union[str, TensorType]] = None						,							A_ :  bool = False  )       ->     Tuple:

       """simple docstring"""






       if not isinstance(A_						,							A_  ):
             lowerCamelCase_							=   TensorType(A_  )

       # 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

             lowerCamelCase_							=   tf.constant
             lowerCamelCase_							=   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

             lowerCamelCase_							=   torch.tensor
             lowerCamelCase_							=   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

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

       # Do the tensor conversion in batch

       try:
             if prepend_batch_axis:
                   lowerCamelCase_							=   [inputs]

             if not is_tensor(A_  ):
                   lowerCamelCase_							=   as_tensor(A_  )
       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 :  Union[str, Any]						,							A_ :  Union[str, Any]						,							A_ :  Optional[int]						,							A_ :  List[str]=""						,							A_ :  Optional[Any]="pt"  )       ->     BatchEncoding:

       """simple docstring"""






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

       lowerCamelCase_					,    lowerCamelCase_					,    lowerCamelCase_							=   self.tokenize(A_						,							A_						,							A_  )
       lowerCamelCase_					,    lowerCamelCase_					,    lowerCamelCase_							=   self._convert_token_to_id(A_						,							A_						,							A_  )

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

 def     a__			(    self :  Tuple						,							A_ :  str						,							A_ :  Optional[str] = None  )       ->     Tuple[str]:

       """simple docstring"""






       if not os.path.isdir(A_  ):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
             return

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

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

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

       return (artists_file, genres_file, lyrics_file)





 def     a__			(    self :  Optional[Any]						,							A_ :  List[str]						,							A_ :  Tuple						,							A_ :  Dict  )       ->     str:

       """simple docstring"""






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









from __future__ import annotations

def       _SCREAMING_SNAKE_CASE      (							lowercase     :	dict     ,							lowercase     :	str					):


      '''simple docstring'''



      lowerCamelCase_					,    lowerCamelCase_							=   set(lowercase					), [start]

      while stack:
            lowerCamelCase_							=   stack.pop()
            explored.add(lowercase					)
            # Differences from BFS:
            # 1) pop last element instead of first one
            # 2) add adjacent elements to stack without exploring them
            for adj in reversed(graph[v]					):
                  if adj not in explored:
                        stack.append(lowercase					)
      return explored


lowerCamelCase    :		int			   =       {
    "A": ["B", "C", "D"],
    "B": ["A", "D", "E"],
    "C": ["A", "F"],
    "D": ["B", "D"],
    "E": ["B", "F"],
    "F": ["C", "E", "G"],
    "G": ["F"],
}

if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(depth_first_search(G, "A"))



