


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


_A			=						logging.get_logger(__name__)

_A			=						{
    'artists_file': 'artists.json',
    'lyrics_file': 'lyrics.json',
    'genres_file': 'genres.json',
}

_A			=						{
    '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',
    },
}

_A			=						{
    'jukebox': 512,
}






class    UpperCAmelCase__	( A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Tuple              =  VOCAB_FILES_NAMES
    UpperCAmelCase__						:		List[Any]              =  PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase__						:		Union[str, Any]              =  PRETRAINED_LYRIC_TOKENS_SIZES
    UpperCAmelCase__						:		List[str]              =  ["input_ids", "attention_mask"]






    def __init__(      self ,       A_ ,       A_ ,       A_ ,       A_=["v3", "v2", "v2"] ,       A_=512 ,       A_=5 ,       A_="<|endoftext|>" ,       **A_ ,       )  ->	Dict:
         __UpperCamelCase   							=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_ ,       )
         __UpperCamelCase   							=version
         __UpperCamelCase   							=max_n_lyric_tokens
         __UpperCamelCase   							=n_genres

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

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

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

         __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(A_   )
         __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 _a (      self   )  ->	Optional[Any]:
         return len(self.artists_encoder   ) + len(self.genres_encoder   ) + len(self.lyrics_encoder   )






    def _a (      self   )  ->	List[str]:
         return dict(self.artists_encoder ,       self.genres_encoder ,       self.lyrics_encoder   )






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

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






    def _a (      self ,       A_   )  ->	Any:
         return list(A_   )






    def _a (      self ,       A_ ,       A_ ,       A_ ,       **A_   )  ->	str:
         __UpperCamelCase							,				__UpperCamelCase							,				__UpperCamelCase   							=self.prepare_for_tokenization(A_ ,       A_ ,       A_   )
         __UpperCamelCase   							=self._tokenize(A_   )
         return artist, genre, lyrics






    def _a (      self ,       A_ ,       A_ ,       A_ ,       A_ = False   )  ->	Tuple[str, str, str, Dict[str, Any]]:
         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(A_   ) + '.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(A_   )   )}
              __UpperCamelCase   							=0
              __UpperCamelCase   							=len(A_   ) + 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(A_   )
         __UpperCamelCase   							=lyrics.replace('\\' ,       '\n'   )
         __UpperCamelCase   							=self.out_of_vocab.sub('' ,       A_   ), [], []
         return artists, genres, lyrics






    def _a (      self ,       A_   )  ->	List[Any]:
         __UpperCamelCase   							=unicodedata.normalize('NFD' ,       A_   )
         __UpperCamelCase   							=[]
         for char in text:
              __UpperCamelCase   							=unicodedata.category(A_   )
              if cat == "Mn":
                   continue
              output.append(A_   )
         return "".join(A_   )






    def _a (      self ,       A_   )  ->	str:
         __UpperCamelCase   							=(
             [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   )]
             + ['.']
         )
         __UpperCamelCase   							=frozenset(A_   )
         __UpperCamelCase   							=re.compile(r'_+'   )
         __UpperCamelCase   							=''.join([c if c in accepted else '_' for c in text.lower()]   )
         __UpperCamelCase   							=pattern.sub('_' ,       A_   ).strip('_'   )
         return text






    def _a (      self ,       A_   )  ->	str:
         return " ".join(A_   )






    def _a (      self ,       A_ ,       A_ = None ,       A_ = False   )  ->	Dict:
         # Convert to TensorType
         if not isinstance(A_ ,       A_   ):
              __UpperCamelCase   							=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

              __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(A_   ):
                   __UpperCamelCase   							=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 ,       A_ ,       A_ ,       A_="" ,       A_="pt"   )  ->	BatchEncoding:
         __UpperCamelCase   							=[0, 0, 0]
         __UpperCamelCase   							=[artist] * len(self.version   )
         __UpperCamelCase   							=[genres] * len(self.version   )

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

         __UpperCamelCase   							=[-INFINITY] * len(full_tokens[-1]   )
         __UpperCamelCase   							=[
             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 ,       A_ ,       A_ = None   )  ->	Tuple[str]:
         if not os.path.isdir(A_   ):
              logger.error(f'Vocabulary path ({save_directory}) should be a directory'   )
              return

         __UpperCamelCase   							=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_   )   )

         __UpperCamelCase   							=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_   )   )

         __UpperCamelCase   							=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 ,       A_ ,       A_ ,       A_   )  ->	int:
         __UpperCamelCase   							=self.artists_decoder.get(A_   )
         __UpperCamelCase   							=[self.genres_decoder.get(A_   ) for genre in genres_index]
         __UpperCamelCase   							=[self.lyrics_decoder.get(A_   ) for character in lyric_index]
         return artist, genres, lyrics









from ....utils import logging


_A			=						logging.get_logger(__name__)






class    UpperCAmelCase__	( A_		):



    """simple docstring"""






    def __init__(      self ,       A_ ,       A_=None ,       A_=2048   )  ->	Any:
         __UpperCamelCase   							=config.__dict__
         __UpperCamelCase   							=modal_hidden_size
         if num_labels:
              __UpperCamelCase   							=num_labels





