



"""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


lowerCAmelCase__              =							logging.get_logger(__name__)

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

lowerCAmelCase__              =							{
    '''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__              =							{
    '''jukebox''': 512,
}






class 			__snake_case			(      _lowercase):
  snake_case__							:  List[Any]         =		VOCAB_FILES_NAMES
  snake_case__							:  int         =		PRETRAINED_VOCAB_FILES_MAP
  snake_case__							:  Optional[Any]         =		PRETRAINED_LYRIC_TOKENS_SIZES
  snake_case__							:  Optional[int]         =		["input_ids", "attention_mask"]




  def __init__(					self	:		str		,   __lowerCAmelCase	:		int		,   __lowerCAmelCase	:		Tuple		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		Optional[int]=["v3", "v2", "v2"]		,   __lowerCAmelCase	:		Any=5_1_2		,   __lowerCAmelCase	:		Tuple=5		,   __lowerCAmelCase	:		List[str]="<|endoftext|>"		,   **__lowerCAmelCase	:		Any		,   ):






         """simple docstring"""






         _lowerCamelCase		:							List[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		,   )
         _lowerCamelCase		:							List[str]            =					version
         _lowerCamelCase		:							List[str]            =					max_n_lyric_tokens
         _lowerCamelCase		:							Optional[Any]            =					n_genres

         with open(__lowerCAmelCase		,   encoding='''utf-8'''						) as vocab_handle:
                _lowerCamelCase		:							Tuple            =					json.load(__lowerCAmelCase						)

         with open(__lowerCAmelCase		,   encoding='''utf-8'''						) as vocab_handle:
                _lowerCamelCase		:							Any            =					json.load(__lowerCAmelCase						)

         with open(__lowerCAmelCase		,   encoding='''utf-8'''						) as vocab_handle:
                _lowerCamelCase		:							List[Any]            =					json.load(__lowerCAmelCase						)

         _lowerCamelCase		:							List[str]            =					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						) == 7_9:
                _lowerCamelCase		:							Optional[Any]            =					oov.replace(R'''\-\''''		,   R'''\-+\''''						)

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




  @property
  def 		SCREAMING_SNAKE_CASE							(					self	:		List[Any]						):






         """simple docstring"""






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




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple						):






         """simple docstring"""






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




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		Optional[Any]		,   __lowerCAmelCase	:		Union[str, Any]						):






         """simple docstring"""






         _lowerCamelCase		:							Union[str, Any]            =					[self.artists_encoder.get(__lowerCAmelCase		,   0						) for artist in list_artists]
         for genres in range(len(__lowerCAmelCase						)						):
                _lowerCamelCase		:							Union[str, Any]            =					[self.genres_encoder.get(__lowerCAmelCase		,   0						) for genre in list_genres[genres]]
                _lowerCamelCase		:							List[str]            =					list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]						))

         _lowerCamelCase		:							Union[str, Any]            =					[[self.lyrics_encoder.get(__lowerCAmelCase		,   0						) for character in list_lyrics[0]], [], []]
         return artists_id, list_genres, lyric_ids




  def 		SCREAMING_SNAKE_CASE							(					self	:		str		,   __lowerCAmelCase	:		Union[str, Any]						):






         """simple docstring"""






         return list(__lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple		,   __lowerCAmelCase	:		List[str]		,   __lowerCAmelCase	:		Any		,   __lowerCAmelCase	:		Tuple		,   **__lowerCAmelCase	:		Union[str, Any]						):






         """simple docstring"""






         _lowerCamelCase     ,       _lowerCamelCase     ,       _lowerCamelCase		:							int            =					self.prepare_for_tokenization(__lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase						)
         _lowerCamelCase		:							Optional[int]            =					self._tokenize(__lowerCAmelCase						)
         return artist, genre, lyrics




  def 		SCREAMING_SNAKE_CASE							(					self	:		Optional[int]		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		bool = False						):






         """simple docstring"""






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

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

         _lowerCamelCase		:							Any            =					self._run_strip_accents(__lowerCAmelCase						)
         _lowerCamelCase		:							Optional[int]            =					lyrics.replace('''\\'''		,   '''\n'''						)
         _lowerCamelCase		:							Optional[int]            =					self.out_of_vocab.sub(''''''		,   __lowerCAmelCase						), [], []
         return artists, genres, lyrics




  def 		SCREAMING_SNAKE_CASE							(					self	:		int		,   __lowerCAmelCase	:		Dict						):






         """simple docstring"""






         _lowerCamelCase		:							Union[str, Any]            =					unicodedata.normalize('''NFD'''		,   __lowerCAmelCase						)
         _lowerCamelCase		:							Optional[int]            =					[]
         for char in text:
                _lowerCamelCase		:							List[str]            =					unicodedata.category(__lowerCAmelCase						)
                if cat == "Mn":
                       continue
                output.append(__lowerCAmelCase						)
         return "".join(__lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple		,   __lowerCAmelCase	:		str						):






         """simple docstring"""






         _lowerCamelCase		:							List[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						)]
             + ['''.''']
         )
         _lowerCamelCase		:							List[Any]            =					frozenset(__lowerCAmelCase						)
         _lowerCamelCase		:							Any            =					re.compile(R'''_+'''						)
         _lowerCamelCase		:							Optional[int]            =					''''''.join([c if c in accepted else '''_''' for c in text.lower()]						)
         _lowerCamelCase		:							List[str]            =					pattern.sub('''_'''		,   __lowerCAmelCase						).strip('''_'''						)
         return text




  def 		SCREAMING_SNAKE_CASE							(					self	:		Dict		,   __lowerCAmelCase	:		List[str]						):






         """simple docstring"""






         return " ".join(__lowerCAmelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Union[str, Any]		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		Optional[Union[str, TensorType]] = None		,   __lowerCAmelCase	:		bool = False						):






         """simple docstring"""






         if not isinstance(__lowerCAmelCase		,   __lowerCAmelCase						):
                _lowerCamelCase		:							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

                _lowerCamelCase		:							Optional[int]            =					tf.constant
                _lowerCamelCase		:							Optional[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

                _lowerCamelCase		:							Any            =					torch.tensor
                _lowerCamelCase		:							Tuple            =					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		:							str            =					jnp.array
                _lowerCamelCase		:							Dict            =					_is_jax
         else:
                _lowerCamelCase		:							Dict            =					np.asarray
                _lowerCamelCase		:							List[str]            =					_is_numpy

         # Do the tensor conversion in batch

         try:
                if prepend_batch_axis:
                       _lowerCamelCase		:							int            =					[inputs]

                if not is_tensor(__lowerCAmelCase						):
                       _lowerCamelCase		:							Dict            =					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	:		Tuple		,   __lowerCAmelCase	:		Union[str, Any]		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		int=""		,   __lowerCAmelCase	:		Union[str, Any]="pt"						):






         """simple docstring"""






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

         _lowerCamelCase     ,       _lowerCamelCase     ,       _lowerCamelCase		:							List[Any]            =					self.tokenize(__lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase						)
         _lowerCamelCase     ,       _lowerCamelCase     ,       _lowerCamelCase		:							Dict            =					self._convert_token_to_id(__lowerCAmelCase		,   __lowerCAmelCase		,   __lowerCAmelCase						)

         _lowerCamelCase		:							Any            =					[-INFINITY] * len(full_tokens[-1]						)
         _lowerCamelCase		:							Optional[int]            =					[
             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 		SCREAMING_SNAKE_CASE							(					self	:		str		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		Optional[str] = None						):






         """simple docstring"""






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

         _lowerCamelCase		:							Optional[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						)						)

         _lowerCamelCase		:							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						)						)

         _lowerCamelCase		:							Optional[Any]            =					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 		SCREAMING_SNAKE_CASE							(					self	:		Optional[Any]		,   __lowerCAmelCase	:		int		,   __lowerCAmelCase	:		Dict		,   __lowerCAmelCase	:		Dict						):






         """simple docstring"""






         _lowerCamelCase		:							str            =					self.artists_decoder.get(__lowerCAmelCase						)
         _lowerCamelCase		:							Optional[Any]            =					[self.genres_decoder.get(__lowerCAmelCase						) for genre in genres_index]
         _lowerCamelCase		:							Optional[int]            =					[self.lyrics_decoder.get(__lowerCAmelCase						) for character in lyric_index]
         return artist, genres, lyrics









from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCamelCase:	List[Any] = logging.get_logger(__name__)

__UpperCamelCase:	Dict = {
    """studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json""",
    """studio-ousia/luke-large""": """https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json""",
}


class       __lowerCAmelCase					(       _UpperCamelCase      ):


	'''simple docstring'''





	_A													=				"luke"

	def __init__(						self:						Union[str, Any],					lowerCamelCase_:						str=50267,					lowerCamelCase_:						Dict=500000,					lowerCamelCase_:						Union[str, Any]=768,					lowerCamelCase_:						Dict=256,					lowerCamelCase_:						int=12,					lowerCamelCase_:						Union[str, Any]=12,					lowerCamelCase_:						str=3072,					lowerCamelCase_:						List[Any]="gelu",					lowerCamelCase_:						int=0.1,					lowerCamelCase_:						Optional[Any]=0.1,					lowerCamelCase_:						Any=512,					lowerCamelCase_:						List[str]=2,					lowerCamelCase_:						str=0.0_2,					lowerCamelCase_:						Union[str, Any]=1E-12,					lowerCamelCase_:						List[Any]=True,					lowerCamelCase_:						List[Any]=None,					lowerCamelCase_:						Optional[Any]=1,					lowerCamelCase_:						Dict=0,					lowerCamelCase_:						List[Any]=2,					**lowerCamelCase_:						Optional[Any],					):
			super().__init__(pad_token_id=lowerCamelCase_,					bos_token_id=lowerCamelCase_,					eos_token_id=lowerCamelCase_,					**lowerCamelCase_			)

			lowercase__					:      Tuple      =		vocab_size
			lowercase__					:      Any      =		entity_vocab_size
			lowercase__					:      Tuple      =		hidden_size
			lowercase__					:      List[str]      =		entity_emb_size
			lowercase__					:      Tuple      =		num_hidden_layers
			lowercase__					:      Optional[Any]      =		num_attention_heads
			lowercase__					:      Dict      =		hidden_act
			lowercase__					:      Optional[int]      =		intermediate_size
			lowercase__					:      List[str]      =		hidden_dropout_prob
			lowercase__					:      Dict      =		attention_probs_dropout_prob
			lowercase__					:      Union[str, Any]      =		max_position_embeddings
			lowercase__					:      int      =		type_vocab_size
			lowercase__					:      Optional[Any]      =		initializer_range
			lowercase__					:      Dict      =		layer_norm_eps
			lowercase__					:      List[Any]      =		use_entity_aware_attention
			lowercase__					:      Optional[Any]      =		classifier_dropout


