
"""simple docstring"""

import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase     :    Optional[int]       =			'''▁'''

UpperCamelCase     :    List[str]       =			{'''vocab_file''': '''spiece.model'''}

UpperCamelCase     :    List[Any]       =			{
    '''vocab_file''': {'''google/pegasus-xsum''': '''https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'''}
}

UpperCamelCase     :    Optional[int]       =			{
    '''google/pegasus-xsum''': 5_1_2,
}


UpperCamelCase     :    Tuple       =			logging.get_logger(__name__)

class __lowerCAmelCase		(				a__      ):
     lowercase						       =						VOCAB_FILES_NAMES

     lowercase						       =						VOCAB_FILES_NAMES
     lowercase						       =						PRETRAINED_VOCAB_FILES_MAP
     lowercase						       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase						       =						["""input_ids""", """attention_mask"""]





     def __init__(     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase="<pad>"     ,					__UpperCAmelCase="</s>"     ,					__UpperCAmelCase="<unk>"     ,					__UpperCAmelCase="<mask_2>"     ,					__UpperCAmelCase="<mask_1>"     ,					__UpperCAmelCase=None     ,					__UpperCAmelCase=103     ,					__UpperCAmelCase = None     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      __UpperCamelCase      =	offset
      if additional_special_tokens is not None:
       if not isinstance(lowerCAmelCase__     ,					lowerCAmelCase__				):
        raise TypeError(
            F'additional_special_tokens should be of type {type(lowerCAmelCase__				)}, but is'
            F' {type(lowerCAmelCase__				)}'				)

       __UpperCamelCase      =	(
           ([mask_token_sent] + additional_special_tokens)
           if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
           else additional_special_tokens
       )
       # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
       additional_special_tokens_extended += [
           F'<unk_{i}>' for i in range(len(lowerCAmelCase__				)     ,					self.offset - 1				)
       ]

       if len(set(lowerCAmelCase__				)				) != len(lowerCAmelCase__				):
        raise ValueError(
            'Please make sure that the provided additional_special_tokens do not contain an incorrectly'
            F' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.'				)
       __UpperCamelCase      =	additional_special_tokens_extended
      else:
       __UpperCamelCase      =	[mask_token_sent] if mask_token_sent is not None else []
       additional_special_tokens += [F'<unk_{i}>' for i in range(2     ,					self.offset				)]

      __UpperCamelCase      =	{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          eos_token=lowerCAmelCase__     ,					unk_token=lowerCAmelCase__     ,					mask_token=lowerCAmelCase__     ,					pad_token=lowerCAmelCase__     ,					mask_token_sent=lowerCAmelCase__     ,					offset=lowerCAmelCase__     ,					additional_special_tokens=lowerCAmelCase__     ,					sp_model_kwargs=self.sp_model_kwargs     ,					**lowerCAmelCase__     ,					)
      __UpperCamelCase      =	mask_token_sent
      __UpperCamelCase      =	vocab_file
      __UpperCamelCase      =	spm.SentencePieceProcessor(**self.sp_model_kwargs				)
      self.sp_model.Load(lowerCAmelCase__				)

      # add special tokens to encoder dict
      __UpperCamelCase      =	{
          0: self.pad_token,
          1: self.eos_token,
      }

      if self.mask_token_sent is not None:
       self.encoder.update(
           {
               2: self.mask_token_sent,
               3: self.mask_token,
           }				)

      if self.offset > 0:
       # entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
       # mask_token_sent is already added to list -> so start at 1
       self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1     ,					self.offset - 1				)}				)

      __UpperCamelCase      =	{v: k for k, v in self.encoder.items()}





     @property
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      return len(self.sp_model				) + self.offset





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	{self.convert_ids_to_tokens(lowerCAmelCase__				): i for i in range(self.vocab_size				)}
      vocab.update(self.added_tokens_encoder				)
      return vocab





     def __getstate__(     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.__dict__.copy()
      __UpperCamelCase      =	None
      return state





     def __setstate__(     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	d

      # for backward compatibility
      if not hasattr(self     ,					'sp_model_kwargs'				):
       __UpperCamelCase      =	{}

      __UpperCamelCase      =	spm.SentencePieceProcessor(**self.sp_model_kwargs				)
      self.sp_model.Load(self.vocab_file				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      return self.sp_model.encode(lowerCAmelCase__     ,					out_type=lowerCAmelCase__				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      if token in self.decoder:
       return self.decoder[token]
      elif token in self.added_tokens_decoder:
       return self.added_tokens_decoder[token]
      __UpperCamelCase      =	self.sp_model.piece_to_id(lowerCAmelCase__				)
      return sp_id + self.offset





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      if index in self.encoder:
       return self.encoder[index]
      elif index in self.added_tokens_encoder:
       return self.added_tokens_encoder[index]
      else:
       __UpperCamelCase      =	self.sp_model.IdToPiece(index - self.offset				)
      return token





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	[]
      __UpperCamelCase      =	""
      for token in tokens:
       # make sure that special tokens are not decoded using sentencepiece model
       if token in self.all_special_tokens:
        out_string += self.sp_model.decode(lowerCAmelCase__				) + token
        __UpperCamelCase      =	[]
       else:
        current_sub_tokens.append(lowerCAmelCase__				)
      out_string += self.sp_model.decode(lowerCAmelCase__				)
      return out_string.strip()





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase=False				):

      '''simple docstring'''




      return 1





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	set(self.all_special_ids				)  # call it once instead of inside list comp
      all_special_ids.remove(self.unk_token_id				)  # <unk> is only sometimes special

      return [1 if x in all_special_ids else 0 for x in seq]





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None     ,					__UpperCAmelCase = False				):

      '''simple docstring'''




      if already_has_special_tokens:
       return self._special_token_mask(lowerCAmelCase__				)
      elif token_ids_a is None:
       return self._special_token_mask(lowerCAmelCase__				) + [1]
      else:
       return self._special_token_mask(token_ids_a + token_ids_a				) + [1]





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase=None				):

      '''simple docstring'''




      if token_ids_a is None:
       return token_ids_a + [self.eos_token_id]
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return token_ids_a + token_ids_a + [self.eos_token_id]







     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




      if not os.path.isdir(lowerCAmelCase__				):
       logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
       return
      __UpperCamelCase      =	os.path.join(
          lowerCAmelCase__     ,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

      if os.path.abspath(self.vocab_file				) != os.path.abspath(lowerCAmelCase__				) and os.path.isfile(self.vocab_file				):
       copyfile(self.vocab_file     ,					lowerCAmelCase__				)
      elif not os.path.isfile(self.vocab_file				):
       with open(lowerCAmelCase__     ,					'wb'				) as fi:
        __UpperCamelCase      =	self.sp_model.serialized_model_proto()
        fi.write(lowerCAmelCase__				)

      return (out_vocab_file,)





"""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


UpperCamelCase     :    Tuple       =			logging.get_logger(__name__)

UpperCamelCase     :    int       =			{
    "artists_file": "artists.json",
    "lyrics_file": "lyrics.json",
    "genres_file": "genres.json",
}

UpperCamelCase     :    Optional[Any]       =			{
    "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     :    Any       =			{
    "jukebox": 5_1_2,
}

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						VOCAB_FILES_NAMES
     lowercase						       =						PRETRAINED_VOCAB_FILES_MAP
     lowercase						       =						PRETRAINED_LYRIC_TOKENS_SIZES
     lowercase						       =						["input_ids", "attention_mask"]





     def __init__(     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase=["v3", "v2", "v2"]     ,					__UpperCAmelCase=512     ,					__UpperCAmelCase=5     ,					__UpperCAmelCase="<|endoftext|>"     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




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

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

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

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

      __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(__UpperCAmelCase				)
      __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 						UpperCAmelCase (     self				):

      '''simple docstring'''




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





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




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





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				):

      '''simple docstring'''




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

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





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      return list(__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					**__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase  ,     __UpperCamelCase  ,     __UpperCamelCase      =	self.prepare_for_tokenization(__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				)
      __UpperCamelCase      =	self._tokenize(__UpperCAmelCase				)
      return artist, genre, lyrics





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase = False				):

      '''simple docstring'''




      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(__UpperCAmelCase				) + '.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(__UpperCAmelCase				)				)}
       __UpperCamelCase      =	0
       __UpperCamelCase      =	len(__UpperCAmelCase				) + 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(__UpperCAmelCase				)
      __UpperCamelCase      =	lyrics.replace('\\'     ,					'\n'				)
      __UpperCamelCase      =	self.out_of_vocab.sub(''     ,					__UpperCAmelCase				), [], []
      return artists, genres, lyrics





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




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





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




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





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase				):

      '''simple docstring'''




      return " ".join(__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None     ,					__UpperCAmelCase = False				):

      '''simple docstring'''




      if not isinstance(__UpperCAmelCase     ,					__UpperCAmelCase				):
       __UpperCamelCase      =	TensorType(__UpperCAmelCase				)

      # 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(__UpperCAmelCase				):
        __UpperCamelCase      =	as_tensor(__UpperCAmelCase				)
      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     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase=""     ,					__UpperCAmelCase="pt"				):

      '''simple docstring'''




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

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

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





     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = None				):

      '''simple docstring'''




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

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

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

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

      return (artists_file, genres_file, lyrics_file)







     def 						UpperCAmelCase (     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					__UpperCAmelCase				):

      '''simple docstring'''




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



