




"""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 			__lowerCamelCase	(   UpperCamelCase__   ):




    """simple docstring"""

    snake_case__ =				VOCAB_FILES_NAMES
    snake_case__ =				PRETRAINED_VOCAB_FILES_MAP
    snake_case__ =				PRETRAINED_LYRIC_TOKENS_SIZES
    snake_case__ =				["input_ids", "attention_mask"]


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

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

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

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

         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(SCREAMING_SNAKE_CASE__       )
         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        a				(	self					:					Dict       )				->	Any:
         return len(self.artists_encoder       ) + len(self.genres_encoder       ) + len(self.lyrics_encoder       )


    def        a				(	self					:					List[Any]       )				->	Dict:
         return dict(self.artists_encoder       ,     self.genres_encoder       ,     self.lyrics_encoder       )


    def        a				(	self					:					Any       ,     SCREAMING_SNAKE_CASE__					:					int       ,     SCREAMING_SNAKE_CASE__					:					List[str]       ,     SCREAMING_SNAKE_CASE__					:					Any       )				->	List[str]:
         lowerCAmelCase__          =			[self.artists_encoder.get(SCREAMING_SNAKE_CASE__       ,     0       ) for artist in list_artists]
         for genres in range(len(SCREAMING_SNAKE_CASE__       )       ):
              lowerCAmelCase__          =			[self.genres_encoder.get(SCREAMING_SNAKE_CASE__       ,     0       ) for genre in list_genres[genres]]
              lowerCAmelCase__          =			list_genres[genres] + [-1] * (self.n_genres - len(list_genres[genres]       ))

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


    def        a				(	self					:					int       ,     SCREAMING_SNAKE_CASE__					:					Union[str, Any]       )				->	int:
         return list(SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					Optional[int]       ,     SCREAMING_SNAKE_CASE__					:					List[str]       ,     SCREAMING_SNAKE_CASE__					:					Any       ,     SCREAMING_SNAKE_CASE__					:					Optional[Any]       ,     **SCREAMING_SNAKE_CASE__					:					List[Any]       )				->	List[str]:
         lowerCAmelCase__     ,		lowerCAmelCase__     ,		lowerCAmelCase__          =			self.prepare_for_tokenization(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			self._tokenize(SCREAMING_SNAKE_CASE__       )
         return artist, genre, lyrics


    def        a				(	self					:					Union[str, Any]       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					bool = 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(SCREAMING_SNAKE_CASE__       ) + ".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(SCREAMING_SNAKE_CASE__       )       )}
              lowerCAmelCase__          =			0
              lowerCAmelCase__          =			len(SCREAMING_SNAKE_CASE__       ) + 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(SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			lyrics.replace("\\"       ,     "\n"       )
         lowerCAmelCase__          =			self.out_of_vocab.sub(""       ,     SCREAMING_SNAKE_CASE__       ), [], []
         return artists, genres, lyrics


    def        a				(	self					:					Dict       ,     SCREAMING_SNAKE_CASE__					:					Tuple       )				->	int:
         lowerCAmelCase__          =			unicodedata.normalize("NFD"       ,     SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			[]
         for char in text:
              lowerCAmelCase__          =			unicodedata.category(SCREAMING_SNAKE_CASE__       )
              if cat == "Mn":
                   continue
              output.append(SCREAMING_SNAKE_CASE__       )
         return "".join(SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					List[str]       ,     SCREAMING_SNAKE_CASE__					:					str       )				->	str:
         lowerCAmelCase__          =			(
             [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       )]
             + ["."]
         )
         lowerCAmelCase__          =			frozenset(SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			re.compile(r"_+"       )
         lowerCAmelCase__          =			"".join([c if c in accepted else "_" for c in text.lower()]       )
         lowerCAmelCase__          =			pattern.sub("_"       ,     SCREAMING_SNAKE_CASE__       ).strip("_"       )
         return text


    def        a				(	self					:					Any       ,     SCREAMING_SNAKE_CASE__					:					List[str]       )				->	str:
         return " ".join(SCREAMING_SNAKE_CASE__       )


    def        a				(	self					:					str       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					Optional[Union[str, TensorType]] = None       ,     SCREAMING_SNAKE_CASE__					:					bool = False       )				->	Any:
         # Convert to TensorType
         if not isinstance(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       ):
              lowerCAmelCase__          =			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

              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(SCREAMING_SNAKE_CASE__       ):
                   lowerCAmelCase__          =			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					:					int       ,     SCREAMING_SNAKE_CASE__					:					List[str]       ,     SCREAMING_SNAKE_CASE__					:					Union[str, Any]       ,     SCREAMING_SNAKE_CASE__					:					Dict=""       ,     SCREAMING_SNAKE_CASE__					:					Any="pt"       )				->	BatchEncoding:
         lowerCAmelCase__          =			[0, 0, 0]
         lowerCAmelCase__          =			[artist] * len(self.version       )
         lowerCAmelCase__          =			[genres] * len(self.version       )

         lowerCAmelCase__     ,		lowerCAmelCase__     ,		lowerCAmelCase__          =			self.tokenize(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__     ,		lowerCAmelCase__     ,		lowerCAmelCase__          =			self._convert_token_to_id(SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       ,     SCREAMING_SNAKE_CASE__       )

         lowerCAmelCase__          =			[-INFINITY] * len(full_tokens[-1]       )
         lowerCAmelCase__          =			[
             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        a				(	self					:					int       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					Optional[str] = None       )				->	Tuple[str]:
         if not os.path.isdir(SCREAMING_SNAKE_CASE__       ):
              logger.error(f'Vocabulary path ({save_directory}) should be a directory'       )
              return

         lowerCAmelCase__          =			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__       )       )

         lowerCAmelCase__          =			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__       )       )

         lowerCAmelCase__          =			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        a				(	self					:					List[str]       ,     SCREAMING_SNAKE_CASE__					:					str       ,     SCREAMING_SNAKE_CASE__					:					Union[str, Any]       ,     SCREAMING_SNAKE_CASE__					:					List[Any]       )				->	Dict:
         lowerCAmelCase__          =			self.artists_decoder.get(SCREAMING_SNAKE_CASE__       )
         lowerCAmelCase__          =			[self.genres_decoder.get(SCREAMING_SNAKE_CASE__       ) for genre in genres_index]
         lowerCAmelCase__          =			[self.lyrics_decoder.get(SCREAMING_SNAKE_CASE__       ) for character in lyric_index]
         return artist, genres, lyrics






import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


UpperCamelCase								=					'__DUMMY_TRANSFORMERS_USER__'
UpperCamelCase								=					'Dummy User'
UpperCamelCase								=					'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'

UpperCamelCase								=					'https://hub-ci.huggingface.co'
UpperCamelCase								=					CI_HUB_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
UpperCamelCase								=					CI_HUB_ENDPOINT + '/{repo_id}/resolve/{revision}/{filename}'
UpperCamelCase								=					Path('~/.huggingface/hub_ci_token').expanduser()



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: Dict      ):
     """simple docstring"""

     monkeypatch.setattr(
         "huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"       ,    lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: int      ):
     """simple docstring"""

     monkeypatch.setattr("datasets.config.HF_ENDPOINT"       ,    lowerCAmelCase_      )
     monkeypatch.setattr("datasets.config.HUB_DATASETS_URL"       ,    lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: str      ):
     """simple docstring"""

     monkeypatch.setattr("huggingface_hub.hf_api.HfFolder.path_token"       ,    lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: int       ,    lowerCAmelCase_					: List[Any]      ):
     """simple docstring"""

     HfFolder.save_token(lowerCAmelCase_      )
     yield
     HfFolder.delete_token()



@pytest.fixture(scope="session"      )
def 							_A       (						):
     """simple docstring"""

     return HfApi(endpoint=lowerCAmelCase_      )



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi      ):
     """simple docstring"""

     lowerCAmelCase__          =			HfFolder.get_token()
     HfFolder.save_token(lowerCAmelCase_      )
     yield CI_HUB_USER_TOKEN
     if previous_token is not None:
          HfFolder.save_token(lowerCAmelCase_      )



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: Tuple      ):
     """simple docstring"""

     def _cleanup_repo(lowerCAmelCase_					: Optional[Any]      ):
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )

     return _cleanup_repo



@pytest.fixture
def 							_A       (						lowerCAmelCase_					: Union[str, Any]      ):
     """simple docstring"""

     @contextmanager
     def _temporary_repo(lowerCAmelCase_					: str      ):
          try:
               yield repo_id
          finally:
               cleanup_repo(lowerCAmelCase_      )

     return _temporary_repo



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi       ,    lowerCAmelCase_					: Union[str, Any]       ,    lowerCAmelCase_					: Any      ):
     """simple docstring"""

     lowerCAmelCase__          =			F'repo_txt_data-{int(time.time() * 1_0E3      )}'
     lowerCAmelCase__          =			F'{CI_HUB_USER}/{repo_name}'
     hf_api.create_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"       ,    private=lowerCAmelCase_      )
     hf_api.upload_file(
         token=lowerCAmelCase_       ,    path_or_fileobj=str(lowerCAmelCase_      )       ,    path_in_repo="data/text_data.txt"       ,    repo_id=lowerCAmelCase_       ,    repo_type="dataset"       ,    )
     yield repo_id
     try:
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass



@pytest.fixture()
def 							_A       (						lowerCAmelCase_					: Optional[Any]       ,    lowerCAmelCase_					: Optional[Any]       ,    lowerCAmelCase_					: int      ):
     """simple docstring"""

     return hf_private_dataset_repo_txt_data_



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi       ,    lowerCAmelCase_					: Tuple       ,    lowerCAmelCase_					: Tuple      ):
     """simple docstring"""

     lowerCAmelCase__          =			F'repo_zipped_txt_data-{int(time.time() * 1_0E3      )}'
     lowerCAmelCase__          =			F'{CI_HUB_USER}/{repo_name}'
     hf_api.create_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"       ,    private=lowerCAmelCase_      )
     hf_api.upload_file(
         token=lowerCAmelCase_       ,    path_or_fileobj=str(lowerCAmelCase_      )       ,    path_in_repo="data.zip"       ,    repo_id=lowerCAmelCase_       ,    repo_type="dataset"       ,    )
     yield repo_id
     try:
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass



@pytest.fixture()
def 							_A       (						lowerCAmelCase_					: int       ,    lowerCAmelCase_					: List[str]       ,    lowerCAmelCase_					: Tuple      ):
     """simple docstring"""

     return hf_private_dataset_repo_zipped_txt_data_



@pytest.fixture(scope="session"      )
def 							_A       (						lowerCAmelCase_					: HfApi       ,    lowerCAmelCase_					: List[str]       ,    lowerCAmelCase_					: int      ):
     """simple docstring"""

     lowerCAmelCase__          =			F'repo_zipped_img_data-{int(time.time() * 1_0E3      )}'
     lowerCAmelCase__          =			F'{CI_HUB_USER}/{repo_name}'
     hf_api.create_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"       ,    private=lowerCAmelCase_      )
     hf_api.upload_file(
         token=lowerCAmelCase_       ,    path_or_fileobj=str(lowerCAmelCase_      )       ,    path_in_repo="data.zip"       ,    repo_id=lowerCAmelCase_       ,    repo_type="dataset"       ,    )
     yield repo_id
     try:
          hf_api.delete_repo(lowerCAmelCase_       ,    token=lowerCAmelCase_       ,    repo_type="dataset"      )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass






@pytest.fixture()
def 							_A       (						lowerCAmelCase_					: Optional[Any]       ,    lowerCAmelCase_					: Dict       ,    lowerCAmelCase_					: List[str]      ):
     """simple docstring"""

     return hf_private_dataset_repo_zipped_img_data_
