import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a  :      Optional[Any]            =    """▁"""

a  :      Dict            =    get_tests_dir("""fixtures/test_sentencepiece.model""")

@require_sentencepiece
class 					_lowercase    (     UpperCAmelCase__ ,  unittest.TestCase			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				Any          =    BertGenerationTokenizer
    SCREAMING_SNAKE_CASE:				List[Any]          =    False
    SCREAMING_SNAKE_CASE:				List[str]          =    True




    def      _a    (    self ):
       super().setUp()

       lowerCAmelCase_:							Union[str, Any]       =	BertGenerationTokenizer(lowerCamelCase__       ,						keep_accents=lowerCamelCase__ )
       tokenizer.save_pretrained(self.tmpdirname )




    def      _a    (    self ):
       lowerCAmelCase_:							Optional[Any]       =	"<s>"
       lowerCAmelCase_:							List[str]       =	1

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase__ )       ,						lowerCamelCase__ )
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase__ )       ,						lowerCamelCase__ )




    def      _a    (    self ):
       lowerCAmelCase_:							Dict       =	list(self.get_tokenizer().get_vocab().keys() )

       self.assertEqual(vocab_keys[0]       ,						"<unk>" )
       self.assertEqual(vocab_keys[1]       ,						"<s>" )
       self.assertEqual(vocab_keys[-1]       ,						"<pad>" )
       self.assertEqual(len(lowerCamelCase__ )       ,						1_002 )




    def      _a    (    self ):
       self.assertEqual(self.get_tokenizer().vocab_size       ,						1_000 )




    def      _a    (    self ):
       lowerCAmelCase_:							Union[str, Any]       =	BertGenerationTokenizer(lowerCamelCase__       ,						keep_accents=lowerCamelCase__ )

       lowerCAmelCase_:							List[Any]       =	tokenizer.tokenize("This is a test" )
       self.assertListEqual(lowerCamelCase__       ,						["▁This", "▁is", "▁a", "▁t", "est"] )

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(lowerCamelCase__ )       ,						[285, 46, 10, 170, 382]       ,						)

       lowerCAmelCase_:							List[str]       =	tokenizer.tokenize("I was born in 92000, and this is falsé." )
       self.assertListEqual(
           lowerCamelCase__       ,						[
               SPIECE_UNDERLINE + "I",
               SPIECE_UNDERLINE + "was",
               SPIECE_UNDERLINE + "b",
               "or",
               "n",
               SPIECE_UNDERLINE + "in",
               SPIECE_UNDERLINE + "",
               "9",
               "2",
               "0",
               "0",
               "0",
               ",",
               SPIECE_UNDERLINE + "and",
               SPIECE_UNDERLINE + "this",
               SPIECE_UNDERLINE + "is",
               SPIECE_UNDERLINE + "f",
               "al",
               "s",
               "é",
               ".",
           ]       ,						)
       lowerCAmelCase_:							str       =	tokenizer.convert_tokens_to_ids(lowerCamelCase__ )
       self.assertListEqual(
           lowerCamelCase__       ,						[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]       ,						)

       lowerCAmelCase_:							str       =	tokenizer.convert_ids_to_tokens(lowerCamelCase__ )
       self.assertListEqual(
           lowerCamelCase__       ,						[
               SPIECE_UNDERLINE + "I",
               SPIECE_UNDERLINE + "was",
               SPIECE_UNDERLINE + "b",
               "or",
               "n",
               SPIECE_UNDERLINE + "in",
               SPIECE_UNDERLINE + "",
               "<unk>",
               "2",
               "0",
               "0",
               "0",
               ",",
               SPIECE_UNDERLINE + "and",
               SPIECE_UNDERLINE + "this",
               SPIECE_UNDERLINE + "is",
               SPIECE_UNDERLINE + "f",
               "al",
               "s",
               "<unk>",
               ".",
           ]       ,						)




    @cached_property
    def      _a    (    self ):
       return BertGenerationTokenizer.from_pretrained("google/bert_for_seq_generation_L-24_bbc_encoder" )




    @slow
    def      _a    (    self ):
       lowerCAmelCase_:							List[str]       =	"Hello World!"
       lowerCAmelCase_:							str       =	[18_536, 2_260, 101]

       self.assertListEqual(lowerCamelCase__       ,						self.big_tokenizer.encode(lowerCamelCase__ ) )




    @slow
    def      _a    (    self ):
       lowerCAmelCase_:							Union[str, Any]       =	(
           "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
           " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
       )
       lowerCAmelCase_:							str       =	[
           871,
           419,
           358,
           946,
           991,
           2_521,
           452,
           358,
           1_357,
           387,
           7_751,
           3_536,
           112,
           985,
           456,
           126,
           865,
           938,
           5_400,
           5_734,
           458,
           1_368,
           467,
           786,
           2_462,
           5_246,
           1_159,
           633,
           865,
           4_519,
           457,
           582,
           852,
           2_557,
           427,
           916,
           508,
           405,
           34_324,
           497,
           391,
           408,
           11_342,
           1_244,
           385,
           100,
           938,
           985,
           456,
           574,
           362,
           12_597,
           3_200,
           3_129,
           1_172,
       ]

       self.assertListEqual(lowerCamelCase__       ,						self.big_tokenizer.encode(lowerCamelCase__ ) )




    @require_torch
    @slow
    def      _a    (    self ):
       import torch

       from transformers import BertGenerationConfig, BertGenerationEncoder

       # Build sequence
       lowerCAmelCase_:							Optional[Any]       =	list(self.big_tokenizer.get_vocab().keys() )[:10]
       lowerCAmelCase_:							Optional[int]       =	" ".join(lowerCamelCase__ )
       lowerCAmelCase_:							List[Any]       =	self.big_tokenizer.encode_plus(lowerCamelCase__       ,						return_tensors="pt"       ,						return_token_type_ids=lowerCamelCase__ )
       lowerCAmelCase_:							Union[str, Any]       =	self.big_tokenizer.batch_encode_plus(
           [sequence + " " + sequence]       ,						return_tensors="pt"       ,						return_token_type_ids=lowerCamelCase__ )

       lowerCAmelCase_:							Optional[Any]       =	BertGenerationConfig()
       lowerCAmelCase_:							List[str]       =	BertGenerationEncoder(lowerCamelCase__ )

       assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

       with torch.no_grad():
          model(**lowerCamelCase__ )
          model(**lowerCamelCase__ )




    @slow
    def      _a    (    self ):
       # fmt: off
       lowerCAmelCase_:							str       =	{"input_ids": [[39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114], [448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=lowerCamelCase__       ,						model_name="google/bert_for_seq_generation_L-24_bbc_encoder"       ,						revision="c817d1fd1be2ffa69431227a1fe320544943d4db"       ,						)
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[Any]            =    logging.get_logger(__name__)

a  :      Optional[Any]            =    {
    """artists_file""": """artists.json""",
    """lyrics_file""": """lyrics.json""",
    """genres_file""": """genres.json""",
}

a  :      str            =    {
    """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  :      Any            =    {
    """jukebox""": 5_1_2,
}

class 					_lowercase    (     UpperCAmelCase__			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				Optional[int]          =    VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE:				Optional[Any]          =    PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE:				List[Any]          =    PRETRAINED_LYRIC_TOKENS_SIZES
    SCREAMING_SNAKE_CASE:				Dict          =    ['input_ids', 'attention_mask']




    def __init__(    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__=["v3", "v2", "v2"]       ,						lowerCamelCase__=512       ,						lowerCamelCase__=5       ,						lowerCamelCase__="<|endoftext|>"       ,						**lowerCamelCase__       ,						):
       lowerCAmelCase_:							List[str]       =	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_:							Any       =	version
       lowerCAmelCase_:							str       =	max_n_lyric_tokens
       lowerCAmelCase_:							Optional[Any]       =	n_genres

       with open(lowerCamelCase__       ,						encoding="utf-8" ) as vocab_handle:
          lowerCAmelCase_:							List[Any]       =	json.load(lowerCamelCase__ )

       with open(lowerCamelCase__       ,						encoding="utf-8" ) as vocab_handle:
          lowerCAmelCase_:							Tuple       =	json.load(lowerCamelCase__ )

       with open(lowerCamelCase__       ,						encoding="utf-8" ) as vocab_handle:
          lowerCAmelCase_:							Tuple       =	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 ) == 79:
          lowerCAmelCase_:							List[Any]       =	oov.replace(R"\-'"       ,						R"\-+'" )

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




    @property
    def      _a    (    self ):
       return len(self.artists_encoder ) + len(self.genres_encoder ) + len(self.lyrics_encoder )




    def      _a    (    self ):
       return dict(self.artists_encoder       ,						self.genres_encoder       ,						self.lyrics_encoder )




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							Union[str, Any]       =	[self.artists_encoder.get(lowerCamelCase__       ,						0 ) for artist in list_artists]
       for genres in range(len(lowerCamelCase__ ) ):
          lowerCAmelCase_:							Tuple       =	[self.genres_encoder.get(lowerCamelCase__       ,						0 ) for genre in list_genres[genres]]
          lowerCAmelCase_:							Any       =	list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres] ))

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




    def      _a    (    self       ,						lowerCamelCase__ ):
       return list(lowerCamelCase__ )




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						**lowerCamelCase__ ):
       lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							Union[str, Any]       =	self.prepare_for_tokenization(lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ )
       lowerCAmelCase_:							Any       =	self._tokenize(lowerCamelCase__ )
       return artist, genre, lyrics




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ = False ):
       for idx in range(len(self.version ) ):
          if self.version[idx] == "v3":
             lowerCAmelCase_:							List[Any]       =	artists[idx].lower()
             lowerCAmelCase_:							Tuple       =	[genres[idx].lower()]
          else:
             lowerCAmelCase_:							Optional[Any]       =	self._normalize(artists[idx] ) + ".v2"
             lowerCAmelCase_:							int       =	[
                 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_:							List[Any]       =	regex.compile(R"[^A-Za-z0-9.,:;!?\-'\"()\[\] \t\n]+" )
          lowerCAmelCase_:							Optional[int]       =	"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789.,:;!?-+'\"()[] \t\n"
          lowerCAmelCase_:							Union[str, Any]       =	{vocab[index]: index + 1 for index in range(len(lowerCamelCase__ ) )}
          lowerCAmelCase_:							List[Any]       =	0
          lowerCAmelCase_:							str       =	len(lowerCamelCase__ ) + 1
          lowerCAmelCase_:							Union[str, Any]       =	self.vocab
          lowerCAmelCase_:							List[str]       =	{v: k for k, v in self.vocab.items()}
          lowerCAmelCase_:							Optional[Any]       =	""
       else:
          lowerCAmelCase_:							Optional[int]       =	regex.compile(R"[^A-Za-z0-9.,:;!?\-+'\"()\[\] \t\n]+" )

       lowerCAmelCase_:							int       =	self._run_strip_accents(lowerCamelCase__ )
       lowerCAmelCase_:							Optional[Any]       =	lyrics.replace("\\"       ,						"\n" )
       lowerCAmelCase_:							List[str]       =	self.out_of_vocab.sub(""       ,						lowerCamelCase__ ), [], []
       return artists, genres, lyrics




    def      _a    (    self       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							int       =	unicodedata.normalize("NFD"       ,						lowerCamelCase__ )
       lowerCAmelCase_:							Any       =	[]
       for char in text:
          lowerCAmelCase_:							Optional[Any]       =	unicodedata.category(lowerCamelCase__ )
          if cat == "Mn":
             continue
          output.append(lowerCamelCase__ )
       return "".join(lowerCamelCase__ )




    def      _a    (    self       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							Tuple       =	(
           [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[str]       =	frozenset(lowerCamelCase__ )
       lowerCAmelCase_:							Any       =	re.compile(R"_+" )
       lowerCAmelCase_:							List[Any]       =	"".join([c if c in accepted else "_" for c in text.lower()] )
       lowerCAmelCase_:							Union[str, Any]       =	pattern.sub("_"       ,						lowerCamelCase__ ).strip("_" )
       return text




    def      _a    (    self       ,						lowerCamelCase__ ):
       return " ".join(lowerCamelCase__ )




    def      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__ = None       ,						lowerCamelCase__ = False ):
       # Convert to TensorType
       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_:							str       =	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_:							Optional[Any]       =	torch.tensor
          lowerCAmelCase_:							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

          lowerCAmelCase_:							Optional[Any]       =	jnp.array
          lowerCAmelCase_:							List[str]       =	_is_jax
       else:
          lowerCAmelCase_:							Optional[int]       =	np.asarray
          lowerCAmelCase_:							int       =	_is_numpy

       # Do the tensor conversion in batch

       try:
          if prepend_batch_axis:
             lowerCAmelCase_:							Any       =	[inputs]

          if not is_tensor(lowerCamelCase__ ):
             lowerCAmelCase_:							Optional[int]       =	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       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__=""       ,						lowerCamelCase__="pt" ):
       lowerCAmelCase_:							Any       =	[0, 0, 0]
       lowerCAmelCase_:							Dict       =	[artist] * len(self.version )
       lowerCAmelCase_:							int       =	[genres] * len(self.version )

       lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							List[str]       =	self.tokenize(lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ )
       lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							str       =	self._convert_token_to_id(lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ )

       lowerCAmelCase_:							List[Any]       =	[-INFINITY] * len(full_tokens[-1] )
       lowerCAmelCase_:							Optional[Any]       =	[
           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      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__ = None ):
       if not os.path.isdir(lowerCamelCase__ ):
          logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
          return

       lowerCAmelCase_:							Dict       =	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_:							Optional[Any]       =	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_:							Dict       =	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      _a    (    self       ,						lowerCamelCase__       ,						lowerCamelCase__       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							str       =	self.artists_decoder.get(lowerCamelCase__ )
       lowerCAmelCase_:							Optional[int]       =	[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