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_			    =							logging.get_logger(__name__)

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

UpperCAmelCase_			    =							{
    '''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_			    =							{
    '''jukebox''': 5_1_2,
}




class  __magic_name__  (		__a    ):





   """simple docstring"""




   lowerCAmelCase      :    str  			=   VOCAB_FILES_NAMES
   lowerCAmelCase      :    Dict  			=   PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase      :    Union[str, Any]  			=   PRETRAINED_LYRIC_TOKENS_SIZES
   lowerCAmelCase      :    Optional[int]  			=   ['''input_ids''', '''attention_mask''']



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



    """simple docstring"""



    _UpperCamelCase:     Optional[Any]							= AddedToken(_lowercase		,  lstrip=_lowercase		,  rstrip=_lowercase							) if isinstance(_lowercase		,  _lowercase							) else unk_token
    super().__init__(
        unk_token=_lowercase		,  n_genres=_lowercase		,  version=_lowercase		,  max_n_lyric_tokens=_lowercase		,  **_lowercase		,  )
    _UpperCamelCase:     Dict							= version
    _UpperCamelCase:     Any							= max_n_lyric_tokens
    _UpperCamelCase:     Tuple							= n_genres

    with open(_lowercase		,  encoding='''utf-8'''							) as vocab_handle:
     _UpperCamelCase:     int							= json.load(_lowercase							)

    with open(_lowercase		,  encoding='''utf-8'''							) as vocab_handle:
     _UpperCamelCase:     Dict							= json.load(_lowercase							)

    with open(_lowercase		,  encoding='''utf-8'''							) as vocab_handle:
     _UpperCamelCase:     Dict							= json.load(_lowercase							)

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

    _UpperCamelCase:     Any							= regex.compile(_lowercase							)
    _UpperCamelCase:     str							= {v: k for k, v in self.artists_encoder.items()}
    _UpperCamelCase:     Optional[int]							= {v: k for k, v in self.genres_encoder.items()}
    _UpperCamelCase:     Dict							= {v: k for k, v in self.lyrics_encoder.items()}



   @property
   def   lowerCAmelCase						(	self					:  Optional[int]							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  Union[str, Any]							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  Optional[Any]		,  _lowercase					:  int		,  _lowercase					:  List[Any]		,  _lowercase					:  Optional[int]							):



    """simple docstring"""



    _UpperCamelCase:     int							= [self.artists_encoder.get(_lowercase		,  0							) for artist in list_artists]
    for genres in range(len(_lowercase							)							):
     _UpperCamelCase:     Any							= [self.genres_encoder.get(_lowercase		,  0							) for genre in list_genres[genres]]
     _UpperCamelCase:     Optional[Any]							= list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]							))

    _UpperCamelCase:     Optional[Any]							= [[self.lyrics_encoder.get(_lowercase		,  0							) for character in list_lyrics[0]], [], []]
    return artists_id, list_genres, lyric_ids



   def   lowerCAmelCase						(	self					:  List[str]		,  _lowercase					:  Tuple							):



    """simple docstring"""



    return list(_lowercase							)



   def   lowerCAmelCase						(	self					:  int		,  _lowercase					:  Optional[int]		,  _lowercase					:  int		,  _lowercase					:  str		,  **_lowercase					:  Union[str, Any]							):



    """simple docstring"""



    _UpperCamelCase	,							_UpperCamelCase	,							_UpperCamelCase:     Union[str, Any]							= self.prepare_for_tokenization(_lowercase		,  _lowercase		,  _lowercase							)
    _UpperCamelCase:     Union[str, Any]							= self._tokenize(_lowercase							)
    return artist, genre, lyrics



   def   lowerCAmelCase						(	self					:  List[Any]		,  _lowercase					:  str		,  _lowercase					:  str		,  _lowercase					:  str		,  _lowercase					:  bool = False							):



    """simple docstring"""



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

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

    _UpperCamelCase:     Union[str, Any]							= self._run_strip_accents(_lowercase							)
    _UpperCamelCase:     List[Any]							= lyrics.replace('''\\'''		,  '''\n'''							)
    _UpperCamelCase:     int							= self.out_of_vocab.sub(''''''		,  _lowercase							), [], []
    return artists, genres, lyrics



   def   lowerCAmelCase						(	self					:  List[str]		,  _lowercase					:  List[Any]							):



    """simple docstring"""



    _UpperCamelCase:     List[str]							= unicodedata.normalize('''NFD'''		,  _lowercase							)
    _UpperCamelCase:     Dict							= []
    for char in text:
     _UpperCamelCase:     Dict							= unicodedata.category(_lowercase							)
     if cat == "Mn":
      continue
     output.append(_lowercase							)
    return "".join(_lowercase							)



   def   lowerCAmelCase						(	self					:  Tuple		,  _lowercase					:  str							):



    """simple docstring"""



    _UpperCamelCase:     List[str]							= (
        [chr(_lowercase							) for i in range(ord('''a'''							)		,  ord('''z'''							) + 1							)]
        + [chr(_lowercase							) for i in range(ord('''A'''							)		,  ord('''Z'''							) + 1							)]
        + [chr(_lowercase							) for i in range(ord('''0'''							)		,  ord('''9'''							) + 1							)]
        + ['''.''']
    )
    _UpperCamelCase:     Optional[Any]							= frozenset(_lowercase							)
    _UpperCamelCase:     Tuple							= re.compile(R'''_+'''							)
    _UpperCamelCase:     str							= ''''''.join([c if c in accepted else '''_''' for c in text.lower()]							)
    _UpperCamelCase:     Optional[Any]							= pattern.sub('''_'''		,  _lowercase							).strip('''_'''							)
    return text



   def   lowerCAmelCase						(	self					:  Tuple		,  _lowercase					:  List[str]							):



    """simple docstring"""



    return " ".join(_lowercase							)



   def   lowerCAmelCase						(	self					:  List[Any]		,  _lowercase					:  Optional[int]		,  _lowercase					:  Optional[Union[str, TensorType]] = None		,  _lowercase					:  bool = False							):



    """simple docstring"""



    if not isinstance(_lowercase		,  _lowercase							):
     _UpperCamelCase:     Dict							= TensorType(_lowercase							)

    # 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:     Optional[Any]							= tf.constant
     _UpperCamelCase:     int							= 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:     List[Any]							= torch.tensor
     _UpperCamelCase:     Optional[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

     _UpperCamelCase:     Tuple							= jnp.array
     _UpperCamelCase:     int							= _is_jax
    else:
     _UpperCamelCase:     int							= np.asarray
     _UpperCamelCase:     Dict							= _is_numpy

    # Do the tensor conversion in batch

    try:
     if prepend_batch_axis:
      _UpperCamelCase:     List[Any]							= [inputs]

     if not is_tensor(_lowercase							):
      _UpperCamelCase:     Optional[int]							= as_tensor(_lowercase							)
    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					:  List[Any]		,  _lowercase					:  List[Any]		,  _lowercase					:  Union[str, Any]		,  _lowercase					:  str=""		,  _lowercase					:  List[Any]="pt"							):



    """simple docstring"""



    _UpperCamelCase:     List[Any]							= [0, 0, 0]
    _UpperCamelCase:     Tuple							= [artist] * len(self.version							)
    _UpperCamelCase:     Any							= [genres] * len(self.version							)

    _UpperCamelCase	,							_UpperCamelCase	,							_UpperCamelCase:     Dict							= self.tokenize(_lowercase		,  _lowercase		,  _lowercase							)
    _UpperCamelCase	,							_UpperCamelCase	,							_UpperCamelCase:     Optional[int]							= self._convert_token_to_id(_lowercase		,  _lowercase		,  _lowercase							)

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



   def   lowerCAmelCase						(	self					:  str		,  _lowercase					:  str		,  _lowercase					:  Optional[str] = None							):



    """simple docstring"""



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

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

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

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

    return (artists_file, genres_file, lyrics_file)



   def   lowerCAmelCase						(	self					:  Dict		,  _lowercase					:  Union[str, Any]		,  _lowercase					:  str		,  _lowercase					:  Optional[Any]							):



    """simple docstring"""



    _UpperCamelCase:     int							= self.artists_decoder.get(_lowercase							)
    _UpperCamelCase:     str							= [self.genres_decoder.get(_lowercase							) for genre in genres_index]
    _UpperCamelCase:     List[Any]							= [self.lyrics_decoder.get(_lowercase							) for character in lyric_index]
    return artist, genres, lyrics
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase_			    =							{'''configuration_xlnet''': ['''XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLNetConfig''']}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							['''XLNetTokenizer''']

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							['''XLNetTokenizerFast''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							[
      '''XLNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''XLNetForMultipleChoice''',
      '''XLNetForQuestionAnswering''',
      '''XLNetForQuestionAnsweringSimple''',
      '''XLNetForSequenceClassification''',
      '''XLNetForTokenClassification''',
      '''XLNetLMHeadModel''',
      '''XLNetModel''',
      '''XLNetPreTrainedModel''',
      '''load_tf_weights_in_xlnet''',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_			    =							[
      '''TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''TFXLNetForMultipleChoice''',
      '''TFXLNetForQuestionAnsweringSimple''',
      '''TFXLNetForSequenceClassification''',
      '''TFXLNetForTokenClassification''',
      '''TFXLNetLMHeadModel''',
      '''TFXLNetMainLayer''',
      '''TFXLNetModel''',
      '''TFXLNetPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_xlnet import XLNetTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_xlnet_fast import XLNetTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_xlnet import (
        XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        XLNetForMultipleChoice,
        XLNetForQuestionAnswering,
        XLNetForQuestionAnsweringSimple,
        XLNetForSequenceClassification,
        XLNetForTokenClassification,
        XLNetLMHeadModel,
        XLNetModel,
        XLNetPreTrainedModel,
        load_tf_weights_in_xlnet,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_xlnet import (
        TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFXLNetForMultipleChoice,
        TFXLNetForQuestionAnsweringSimple,
        TFXLNetForSequenceClassification,
        TFXLNetForTokenClassification,
        TFXLNetLMHeadModel,
        TFXLNetMainLayer,
        TFXLNetModel,
        TFXLNetPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase_			    =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)