



"""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


A_						:    List[str]				=      logging.get_logger(__name__)

A_						:    Union[str, Any]				=      {
    'artists_file': 'artists.json',
    'lyrics_file': 'lyrics.json',
    'genres_file': 'genres.json',
}

A_						:    int				=      {
    '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_						:    Union[str, Any]				=      {
    'jukebox': 512,
}
class     lowerCAmelCase__						(	_lowerCamelCase ):


	'''simple docstring'''







	_SCREAMING_SNAKE_CASE	:		List[str]  						= VOCAB_FILES_NAMES
	_SCREAMING_SNAKE_CASE	:		Any  						= PRETRAINED_VOCAB_FILES_MAP
	_SCREAMING_SNAKE_CASE	:		Union[str, Any]  						= PRETRAINED_LYRIC_TOKENS_SIZES
	_SCREAMING_SNAKE_CASE	:		str  						= ['''input_ids''', '''attention_mask''']





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





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							List[Any]							=     AddedToken(_SCREAMING_SNAKE_CASE     ,       lstrip=_SCREAMING_SNAKE_CASE     ,       rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE    ) else unk_token
					super().__init__(
					    unk_token=_SCREAMING_SNAKE_CASE     ,       n_genres=_SCREAMING_SNAKE_CASE     ,       version=_SCREAMING_SNAKE_CASE     ,       max_n_lyric_tokens=_SCREAMING_SNAKE_CASE     ,       **_SCREAMING_SNAKE_CASE     ,       )
					SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     version
					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     max_n_lyric_tokens
					SCREAMING_SNAKE_CASE						:							Optional[int]							=     n_genres

					with open(_SCREAMING_SNAKE_CASE     ,       encoding='utf-8'    ) as vocab_handle:
									SCREAMING_SNAKE_CASE						:							List[str]							=     json.load(_SCREAMING_SNAKE_CASE    )

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

					with open(_SCREAMING_SNAKE_CASE     ,       encoding='utf-8'    ) as vocab_handle:
									SCREAMING_SNAKE_CASE						:							Optional[int]							=     json.load(_SCREAMING_SNAKE_CASE    )

					SCREAMING_SNAKE_CASE						:							Tuple							=     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:
									SCREAMING_SNAKE_CASE						:							Union[str, Any]							=     oov.replace(R'\-\''     ,       R'\-+\''    )

					SCREAMING_SNAKE_CASE						:							str							=     regex.compile(_SCREAMING_SNAKE_CASE    )
					SCREAMING_SNAKE_CASE						:							List[Any]							=     {v: k for k, v in self.artists_encoder.items()}
					SCREAMING_SNAKE_CASE						:							List[str]							=     {v: k for k, v in self.genres_encoder.items()}
					SCREAMING_SNAKE_CASE						:							Tuple							=     {v: k for k, v in self.lyrics_encoder.items()}





	@property
	def 			_lowerCAmelCase     (      self				:       Any    )						->	List[str]:





					"""simple docstring"""


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





	def 			_lowerCAmelCase     (      self				:       Optional[int]    )						->	Any:





					"""simple docstring"""


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





	def 			_lowerCAmelCase     (      self				:       Optional[Any]     ,       _SCREAMING_SNAKE_CASE				:       str     ,       _SCREAMING_SNAKE_CASE				:       Optional[int]     ,       _SCREAMING_SNAKE_CASE				:       Tuple    )						->	Optional[Any]:





					"""simple docstring"""


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

					SCREAMING_SNAKE_CASE						:							Optional[int]							=     [[self.lyrics_encoder.get(_SCREAMING_SNAKE_CASE     ,       0    ) for character in list_lyrics[0]], [], []]
					return artists_id, list_genres, lyric_ids





	def 			_lowerCAmelCase     (      self				:       List[str]     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]    )						->	Dict:





					"""simple docstring"""


					return list(_SCREAMING_SNAKE_CASE    )





	def 			_lowerCAmelCase     (      self				:       Union[str, Any]     ,       _SCREAMING_SNAKE_CASE				:       int     ,       _SCREAMING_SNAKE_CASE				:       Tuple     ,       _SCREAMING_SNAKE_CASE				:       Tuple     ,       **_SCREAMING_SNAKE_CASE				:       Optional[int]    )						->	str:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						:							Tuple							=     self.prepare_for_tokenization(_SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE    )
					SCREAMING_SNAKE_CASE						:							Dict							=     self._tokenize(_SCREAMING_SNAKE_CASE    )
					return artist, genre, lyrics





	def 			_lowerCAmelCase     (      self				:       Optional[int]     ,       _SCREAMING_SNAKE_CASE				:       str     ,       _SCREAMING_SNAKE_CASE				:       str     ,       _SCREAMING_SNAKE_CASE				:       str     ,       _SCREAMING_SNAKE_CASE				:       bool = False    )						->	Tuple[str, str, str, Dict[str, Any]]:





					"""simple docstring"""


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

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

					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     self._run_strip_accents(_SCREAMING_SNAKE_CASE    )
					SCREAMING_SNAKE_CASE						:							List[str]							=     lyrics.replace('\\'     ,       '\n'    )
					SCREAMING_SNAKE_CASE						:							List[Any]							=     self.out_of_vocab.sub(''     ,       _SCREAMING_SNAKE_CASE    ), [], []
					return artists, genres, lyrics





	def 			_lowerCAmelCase     (      self				:       str     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]    )						->	Optional[Any]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							Any							=     unicodedata.normalize('NFD'     ,       _SCREAMING_SNAKE_CASE    )
					SCREAMING_SNAKE_CASE						:							Optional[int]							=     []
					for char in text:
									SCREAMING_SNAKE_CASE						:							Dict							=     unicodedata.category(_SCREAMING_SNAKE_CASE    )
									if cat == "Mn":
													continue
									output.append(_SCREAMING_SNAKE_CASE    )
					return "".join(_SCREAMING_SNAKE_CASE    )





	def 			_lowerCAmelCase     (      self				:       Any     ,       _SCREAMING_SNAKE_CASE				:       str    )						->	str:





					"""simple docstring"""


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





	def 			_lowerCAmelCase     (      self				:       Dict     ,       _SCREAMING_SNAKE_CASE				:       List[str]    )						->	str:





					"""simple docstring"""


					return " ".join(_SCREAMING_SNAKE_CASE    )





	def 			_lowerCAmelCase     (      self				:       Dict     ,       _SCREAMING_SNAKE_CASE				:       str     ,       _SCREAMING_SNAKE_CASE				:       Optional[Union[str, TensorType]] = None     ,       _SCREAMING_SNAKE_CASE				:       bool = False    )						->	Tuple:





					"""simple docstring"""


					if not isinstance(_SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE    ):
									SCREAMING_SNAKE_CASE						:							Dict							=     TensorType(_SCREAMING_SNAKE_CASE    )

					# 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

									SCREAMING_SNAKE_CASE						:							int							=     tf.constant
									SCREAMING_SNAKE_CASE						:							Tuple							=     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

									SCREAMING_SNAKE_CASE						:							Any							=     torch.tensor
									SCREAMING_SNAKE_CASE						:							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

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

					# Do the tensor conversion in batch

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

									if not is_tensor(_SCREAMING_SNAKE_CASE    ):
													SCREAMING_SNAKE_CASE						:							str							=     as_tensor(_SCREAMING_SNAKE_CASE    )
					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				:       Tuple     ,       _SCREAMING_SNAKE_CASE				:       List[str]     ,       _SCREAMING_SNAKE_CASE				:       Optional[int]     ,       _SCREAMING_SNAKE_CASE				:       Optional[Any]=""     ,       _SCREAMING_SNAKE_CASE				:       List[str]="pt"    )						->	BatchEncoding:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							int							=     [0, 0, 0]
					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     [artist] * len(self.version    )
					SCREAMING_SNAKE_CASE						:							Any							=     [genres] * len(self.version    )

					SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						:							str							=     self.tokenize(_SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE    )
					SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						:							str							=     self._convert_token_to_id(_SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE    )

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





	def 			_lowerCAmelCase     (      self				:       Union[str, Any]     ,       _SCREAMING_SNAKE_CASE				:       str     ,       _SCREAMING_SNAKE_CASE				:       Optional[str] = None    )						->	Tuple[str]:





					"""simple docstring"""


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

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

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

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

					return (artists_file, genres_file, lyrics_file)







	def 			_lowerCAmelCase     (      self				:       List[str]     ,       _SCREAMING_SNAKE_CASE				:       Dict     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]     ,       _SCREAMING_SNAKE_CASE				:       Union[str, Any]    )						->	Tuple:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE						:							List[str]							=     self.artists_decoder.get(_SCREAMING_SNAKE_CASE    )
					SCREAMING_SNAKE_CASE						:							Optional[Any]							=     [self.genres_decoder.get(_SCREAMING_SNAKE_CASE    ) for genre in genres_index]
					SCREAMING_SNAKE_CASE						:							Dict							=     [self.lyrics_decoder.get(_SCREAMING_SNAKE_CASE    ) for character in lyric_index]
					return artist, genres, lyrics










"""simple docstring"""

from typing import TYPE_CHECKING

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


A_						:    Optional[int]				=      {
    'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LlamaConfig'],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    int				=      ['LlamaTokenizer']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    List[str]				=      ['LlamaTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A_						:    List[str]				=      [
							    'LlamaForCausalLM',
							    'LlamaModel',
							    'LlamaPreTrainedModel',
							    'LlamaForSequenceClassification',
							]


if TYPE_CHECKING:
							from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama import LlamaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_llama_fast import LlamaTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
							import sys

							A_						:    str				=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





