



'''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     		=   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': 512,
}

class __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						UpperCAmelCase							:   Optional[int]									=		VOCAB_FILES_NAMES
						UpperCAmelCase							:   Any									=		PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase							:   Tuple									=		PRETRAINED_LYRIC_TOKENS_SIZES
						UpperCAmelCase							:   Tuple									=		["input_ids", "attention_mask"]


						def __init__( self     ,	A_     ,	A_     ,	A_     ,	A_=["v3", "v2", "v2"]     ,	A_=512     ,	A_=5     ,	A_="<|endoftext|>"     ,	**A_     ,	)     ->     List[str]:
							lowerCAmelCase   =     AddedToken(A_     ,	lstrip=A_     ,	rstrip=A_				) if isinstance(A_     ,	A_				) else unk_token
							super().__init__(
							    unk_token=A_     ,	n_genres=A_     ,	version=A_     ,	max_n_lyric_tokens=A_     ,	**A_     ,	)
							lowerCAmelCase   =     version
							lowerCAmelCase   =     max_n_lyric_tokens
							lowerCAmelCase   =     n_genres

							with open(A_     ,	encoding="""utf-8"""				) as vocab_handle:
								lowerCAmelCase   =     json.load(A_				)

							with open(A_     ,	encoding="""utf-8"""				) as vocab_handle:
								lowerCAmelCase   =     json.load(A_				)

							with open(A_     ,	encoding="""utf-8"""				) as vocab_handle:
								lowerCAmelCase   =     json.load(A_				)

							lowerCAmelCase   =     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   =     oov.replace(r"""\-'"""     ,	r"""\-+'"""				)

							lowerCAmelCase   =     regex.compile(A_				)
							lowerCAmelCase   =     {v: k for k, v in self.artists_encoder.items()}
							lowerCAmelCase   =     {v: k for k, v in self.genres_encoder.items()}
							lowerCAmelCase   =     {v: k for k, v in self.lyrics_encoder.items()}


						@property
						def     __snake_case   ( self				)     ->     Union[str, Any]:
							return len(self.artists_encoder				) + len(self.genres_encoder				) + len(self.lyrics_encoder				)


						def     __snake_case   ( self				)     ->     Optional[int]:
							return dict(self.artists_encoder     ,	self.genres_encoder     ,	self.lyrics_encoder				)


						def     __snake_case   ( self     ,	A_     ,	A_     ,	A_				)     ->     Optional[int]:
							lowerCAmelCase   =     [self.artists_encoder.get(A_     ,	0				) for artist in list_artists]
							for genres in range(len(A_				)				):
								lowerCAmelCase   =     [self.genres_encoder.get(A_     ,	0				) for genre in list_genres[genres]]
								lowerCAmelCase   =     list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]				))

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


						def     __snake_case   ( self     ,	A_				)     ->     Tuple:
							return list(A_				)


						def     __snake_case   ( self     ,	A_     ,	A_     ,	A_     ,	**A_				)     ->     Union[str, Any]:
							lowerCAmelCase,       lowerCAmelCase,       lowerCAmelCase   =     self.prepare_for_tokenization(A_     ,	A_     ,	A_				)
							lowerCAmelCase   =     self._tokenize(A_				)
							return artist, genre, lyrics


						def     __snake_case   ( self     ,	A_     ,	A_     ,	A_     ,	A_ = False				)     ->     Tuple[str, str, str, Dict[str, Any]]:
							for idx in range(len(self.version				)				):
								if self.version[idx] == "v3":
									lowerCAmelCase   =     artists[idx].lower()
									lowerCAmelCase   =     [genres[idx].lower()]
								else:
									lowerCAmelCase   =     self._normalize(artists[idx]				) + """.v2"""
									lowerCAmelCase   =     [
									    self._normalize(A_				) + """.v2""" for genre in genres[idx].split("""_"""				)
									]  # split is for the full dictionary with combined genres

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

							lowerCAmelCase   =     self._run_strip_accents(A_				)
							lowerCAmelCase   =     lyrics.replace("""\\"""     ,	"""\n"""				)
							lowerCAmelCase   =     self.out_of_vocab.sub(""""""     ,	A_				), [], []
							return artists, genres, lyrics


						def     __snake_case   ( self     ,	A_				)     ->     List[Any]:
							lowerCAmelCase   =     unicodedata.normalize("""NFD"""     ,	A_				)
							lowerCAmelCase   =     []
							for char in text:
								lowerCAmelCase   =     unicodedata.category(A_				)
								if cat == "Mn":
									continue
								output.append(A_				)
							return "".join(A_				)


						def     __snake_case   ( self     ,	A_				)     ->     str:
							lowerCAmelCase   =     (
							    [chr(A_				) for i in range(ord("""a"""				)     ,	ord("""z"""				) + 1				)]
							    + [chr(A_				) for i in range(ord("""A"""				)     ,	ord("""Z"""				) + 1				)]
							    + [chr(A_				) for i in range(ord("""0"""				)     ,	ord("""9"""				) + 1				)]
							    + ["""."""]
							)
							lowerCAmelCase   =     frozenset(A_				)
							lowerCAmelCase   =     re.compile(r"""_+"""				)
							lowerCAmelCase   =     """""".join([c if c in accepted else """_""" for c in text.lower()]				)
							lowerCAmelCase   =     pattern.sub("""_"""     ,	A_				).strip("""_"""				)
							return text


						def     __snake_case   ( self     ,	A_				)     ->     str:
							return " ".join(A_				)


						def     __snake_case   ( self     ,	A_     ,	A_ = None     ,	A_ = False				)     ->     Dict:
							# Convert to TensorType
							if not isinstance(A_     ,	A_				):
								lowerCAmelCase   =     TensorType(A_				)

							# 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   =     tf.constant
								lowerCAmelCase   =     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   =     torch.tensor
								lowerCAmelCase   =     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   =     jnp.array
								lowerCAmelCase   =     _is_jax
							else:
								lowerCAmelCase   =     np.asarray
								lowerCAmelCase   =     _is_numpy

							# Do the tensor conversion in batch

							try:
								if prepend_batch_axis:
									lowerCAmelCase   =     [inputs]

								if not is_tensor(A_				):
									lowerCAmelCase   =     as_tensor(A_				)
							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     ,	A_     ,	A_     ,	A_=""     ,	A_="pt"				)     ->     BatchEncoding:
							lowerCAmelCase   =     [0, 0, 0]
							lowerCAmelCase   =     [artist] * len(self.version				)
							lowerCAmelCase   =     [genres] * len(self.version				)

							lowerCAmelCase,       lowerCAmelCase,       lowerCAmelCase   =     self.tokenize(A_     ,	A_     ,	A_				)
							lowerCAmelCase,       lowerCAmelCase,       lowerCAmelCase   =     self._convert_token_to_id(A_     ,	A_     ,	A_				)

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


						def     __snake_case   ( self     ,	A_     ,	A_ = None				)     ->     Tuple[str]:
							if not os.path.isdir(A_				):
								logger.error(f'Vocabulary path ({save_directory}) should be a directory'				)
								return

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

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

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

							return (artists_file, genres_file, lyrics_file)




						def     __snake_case   ( self     ,	A_     ,	A_     ,	A_				)     ->     str:
							lowerCAmelCase   =     self.artists_decoder.get(A_				)
							lowerCAmelCase   =     [self.genres_decoder.get(A_				) for genre in genres_index]
							lowerCAmelCase   =     [self.lyrics_decoder.get(A_				) for character in lyric_index]
							return artist, genres, lyrics




'''simple docstring'''

import pytest

import datasets


# Import fixture modules as plugins
UpperCAmelCase     		=   ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						int							)      ->						Optional[int]:







	"""simple docstring"""
	# Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
	for item in items:
		if any(marker in item.keywords for marker in ["""integration""", """unit"""]							):
			continue
		item.add_marker(pytest.mark.unit							)






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						List[str]							)      ->						Any:







	"""simple docstring"""
	config.addinivalue_line("""markers"""							,		"""torchaudio_latest: mark test to run with torchaudio>=0.12"""							)






@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE							)
def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						Dict							,		_SCREAMING_SNAKE_CASE					:						Dict							)      ->						str:







	"""simple docstring"""
	# test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
	lowerCAmelCase   =     tmp_path_factory.getbasetemp() / """cache"""
	lowerCAmelCase   =     test_hf_cache_home / """datasets"""
	lowerCAmelCase   =     test_hf_cache_home / """metrics"""
	lowerCAmelCase   =     test_hf_cache_home / """modules"""
	monkeypatch.setattr("""datasets.config.HF_DATASETS_CACHE"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	monkeypatch.setattr("""datasets.config.HF_METRICS_CACHE"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	monkeypatch.setattr("""datasets.config.HF_MODULES_CACHE"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	lowerCAmelCase   =     test_hf_datasets_cache / """downloads"""
	monkeypatch.setattr("""datasets.config.DOWNLOADED_DATASETS_PATH"""							,		str(_SCREAMING_SNAKE_CASE							)							)
	lowerCAmelCase   =     test_hf_datasets_cache / """downloads""" / """extracted"""
	monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_PATH"""							,		str(_SCREAMING_SNAKE_CASE							)							)






@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE							,		scope="""session"""							)
def 		_snake_case		( )      ->						Optional[Any]:







	"""simple docstring"""
	datasets.disable_progress_bar()






@pytest.fixture(autouse=_SCREAMING_SNAKE_CASE							)
def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						Any							)      ->						Optional[int]:







	"""simple docstring"""
	# don't take tests into account when counting downloads
	monkeypatch.setattr("""datasets.config.HF_UPDATE_DOWNLOAD_COUNTS"""							,		_SCREAMING_SNAKE_CASE							)






@pytest.fixture
def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						List[str]							)      ->						str:







	"""simple docstring"""
	# Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
	# To be removed once SQLAlchemy 2.0 supported
	monkeypatch.setattr("""sqlalchemy.util.deprecations.SILENCE_UBER_WARNING"""							,		_SCREAMING_SNAKE_CASE							)