


'''simple docstring'''


import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


lowerCamelCase__					=   '\\n    Text data.\n    Second line of data.'

lowerCamelCase__					=   'file'






@pytest.fixture(scope="session"      )
def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				Any	    =					tmp_path_factory.mktemp("data"      ) / (FILE_PATH + ".zstd")
		_UpperCAmelCase						:				Optional[int]	    =					bytes(__lowerCAmelCase					,       "utf-8"      )
		with zstd.open(__lowerCAmelCase					,       "wb"      ) as f:
				f.write(__lowerCAmelCase      )
		return path






@pytest.fixture
def        __lowerCAmelCase       (__lowerCAmelCase      ):
		with open(os.path.join(tmpfs.local_root_dir					,       __lowerCAmelCase      )					,       "w"      ) as f:
				f.write(__lowerCAmelCase      )
		return FILE_PATH






@pytest.mark.parametrize("compression_format"					,       ["gzip", "xz", "zstd"]      )
def        __lowerCAmelCase       (__lowerCAmelCase					,       __lowerCAmelCase					,       __lowerCAmelCase					,       __lowerCAmelCase					,       __lowerCAmelCase					,       __lowerCAmelCase      ):
		_UpperCAmelCase						:				Tuple	    =					{"gzip": gz_file, "xz": xz_file, "zstd": zstd_path}
		_UpperCAmelCase						:				Tuple	    =					input_paths[compression_format]
		_UpperCAmelCase						:				Optional[Any]	    =					tmp_path / "cache"
		_UpperCAmelCase						:				Union[str, Any]	    =					DownloadConfig(cache_dir=__lowerCAmelCase					,       extract_compressed_file=__lowerCAmelCase      )
		_UpperCAmelCase						:				Optional[int]	    =					cached_path(__lowerCAmelCase					,       download_config=__lowerCAmelCase      )
		with open(__lowerCAmelCase      ) as f:
				_UpperCAmelCase						:				Union[str, Any]	    =					f.read()
		with open(__lowerCAmelCase      ) as f:
				_UpperCAmelCase						:				Optional[int]	    =					f.read()
		assert extracted_file_content == expected_file_content






@pytest.mark.parametrize("default_extracted"					,       [True, False]      )
@pytest.mark.parametrize("default_cache_dir"					,       [True, False]      )
def        __lowerCAmelCase       (__lowerCAmelCase					,       __lowerCAmelCase					,       __lowerCAmelCase					,       __lowerCAmelCase					,       __lowerCAmelCase      ):
		_UpperCAmelCase						:				List[Any]	    =					"custom_cache"
		_UpperCAmelCase						:				List[str]	    =					"custom_extracted_dir"
		_UpperCAmelCase						:				str	    =					tmp_path / "custom_extracted_path"
		if default_extracted:
				_UpperCAmelCase						:				Optional[Any]	    =					("downloads" if default_cache_dir else custom_cache_dir, "extracted")
		else:
				monkeypatch.setattr("datasets.config.EXTRACTED_DATASETS_DIR"					,       __lowerCAmelCase      )
				monkeypatch.setattr("datasets.config.EXTRACTED_DATASETS_PATH"					,       str(__lowerCAmelCase      )      )
				_UpperCAmelCase						:				Optional[int]	    =					custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

		_UpperCAmelCase						:				int	    =					xz_file
		_UpperCAmelCase						:				Tuple	    =					(
		    DownloadConfig(extract_compressed_file=__lowerCAmelCase      )
		    if default_cache_dir
		    else DownloadConfig(cache_dir=tmp_path / custom_cache_dir					,       extract_compressed_file=__lowerCAmelCase      )
		)
		_UpperCAmelCase						:				Optional[int]	    =					cached_path(__lowerCAmelCase					,       download_config=__lowerCAmelCase      )
		assert Path(__lowerCAmelCase      ).parent.parts[-2:] == expected






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		# absolute path
		_UpperCAmelCase						:				Optional[Any]	    =					str(Path(__lowerCAmelCase      ).resolve()      )
		assert cached_path(__lowerCAmelCase      ) == text_file
		# relative path
		_UpperCAmelCase						:				str	    =					str(Path(__lowerCAmelCase      ).resolve().relative_to(Path(os.getcwd()      )      )      )
		assert cached_path(__lowerCAmelCase      ) == text_file






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		# absolute path
		_UpperCAmelCase						:				Dict	    =					str(tmp_path.resolve() / "__missing_file__.txt"      )
		with pytest.raises(__lowerCAmelCase      ):
				cached_path(__lowerCAmelCase      )
		# relative path
		_UpperCAmelCase						:				str	    =					"./__missing_file__.txt"
		with pytest.raises(__lowerCAmelCase      ):
				cached_path(__lowerCAmelCase      )






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				Union[str, Any]	    =					get_from_cache(F"""tmp://{tmpfs_file}"""      )
		with open(__lowerCAmelCase      ) as f:
				_UpperCAmelCase						:				List[str]	    =					f.read()
		assert output_file_content == FILE_CONTENT






@patch("datasets.config.HF_DATASETS_OFFLINE"					,       __lowerCAmelCase      )
def        __lowerCAmelCase       ():
		with pytest.raises(__lowerCAmelCase      ):
				cached_path("https://huggingface.co"      )






@patch("datasets.config.HF_DATASETS_OFFLINE"					,       __lowerCAmelCase      )
def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				Any	    =					tmp_path_factory.mktemp("data"      ) / "file.html"
		with pytest.raises(__lowerCAmelCase      ):
				http_get("https://huggingface.co"					,       temp_file=__lowerCAmelCase      )
		with pytest.raises(__lowerCAmelCase      ):
				http_head("https://huggingface.co"      )






@patch("datasets.config.HF_DATASETS_OFFLINE"					,       __lowerCAmelCase      )
def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				Optional[Any]	    =					tmp_path_factory.mktemp("data"      ) / "file.html"
		with pytest.raises(__lowerCAmelCase      ):
				ftp_get("ftp://huggingface.co"					,       temp_file=__lowerCAmelCase      )
		with pytest.raises(__lowerCAmelCase      ):
				ftp_head("ftp://huggingface.co"      )






@patch("datasets.config.HF_DATASETS_OFFLINE"					,       __lowerCAmelCase      )
def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				List[str]	    =					tmp_path_factory.mktemp("data"      ) / "file.html"
		with pytest.raises(__lowerCAmelCase      ):
				fsspec_get("s3://huggingface.co"					,       temp_file=__lowerCAmelCase      )
		with pytest.raises(__lowerCAmelCase      ):
				fsspec_head("s3://huggingface.co"      )







'''simple docstring'''


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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCamelCase__					=   logging.get_logger(__name__)

lowerCamelCase__					=   {'vocab_file': 'sentencepiece.bpe.model'}

lowerCamelCase__					=   {
    'vocab_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'
        ),
    },
}

lowerCamelCase__					=   {
    'moussaKam/mbarthez': 1_024,
    'moussaKam/barthez': 1_024,
    'moussaKam/barthez-orangesum-title': 1_024,
}

lowerCamelCase__					=   '▁'






class 		lowerCAmelCase__	(	UpperCAmelCase__		):
			lowerCAmelCase       :		Any				      =   VOCAB_FILES_NAMES
			lowerCAmelCase       :		Any				      =   PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase       :		Union[str, Any]				      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase       :		int				      =   ["input_ids", "attention_mask"]




			def __init__(						self     :   int		,     lowerCamelCase__     :   Tuple		,     lowerCamelCase__     :   List[Any]="<s>"		,     lowerCamelCase__     :   Dict="</s>"		,     lowerCamelCase__     :   Union[str, Any]="</s>"		,     lowerCamelCase__     :   List[Any]="<s>"		,     lowerCamelCase__     :   List[str]="<unk>"		,     lowerCamelCase__     :   str="<pad>"		,     lowerCamelCase__     :   Tuple="<mask>"		,     lowerCamelCase__     :   Optional[Dict[str, Any]] = None		,     **lowerCamelCase__     :   Dict		,     )      ->None:



					'''simple docstring'''







					_UpperCAmelCase						:				Dict	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else mask_token

					_UpperCAmelCase						:				Any	    =					{} if sp_model_kwargs is None else sp_model_kwargs

					super().__init__(
					    bos_token=lowerCamelCase__		,     eos_token=lowerCamelCase__		,     unk_token=lowerCamelCase__		,     sep_token=lowerCamelCase__		,     cls_token=lowerCamelCase__		,     pad_token=lowerCamelCase__		,     mask_token=lowerCamelCase__		,     sp_model_kwargs=self.sp_model_kwargs		,     **lowerCamelCase__		,     )

					_UpperCAmelCase						:				Union[str, Any]	    =					vocab_file
					_UpperCAmelCase						:				Dict	    =					spm.SentencePieceProcessor(**self.sp_model_kwargs       )
					self.sp_model.Load(str(lowerCamelCase__       )       )

					_UpperCAmelCase						:				Optional[int]	    =					{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

					_UpperCAmelCase						:				List[str]	    =					len(self.sp_model       ) - 1
					_UpperCAmelCase						:				List[str]	    =					{v: k for k, v in self.fairseq_tokens_to_ids.items()}




			def 							lowerCAmelCase__			(						self     :   Dict		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					if token_ids_a is None:
							return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					_UpperCAmelCase						:				Union[str, Any]	    =					[self.cls_token_id]
					_UpperCAmelCase						:				str	    =					[self.sep_token_id]
					return cls + token_ids_a + sep + sep + token_ids_a + sep




			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None		,     lowerCamelCase__     :   bool = False       )      ->List[int]:



					'''simple docstring'''







					if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=lowerCamelCase__		,     token_ids_a=lowerCamelCase__		,     already_has_special_tokens=lowerCamelCase__       )

					if token_ids_a is None:
							return [1] + ([0] * len(lowerCamelCase__       )) + [1]
					return [1] + ([0] * len(lowerCamelCase__       )) + [1, 1] + ([0] * len(lowerCamelCase__       )) + [1]




			def 							lowerCAmelCase__			(						self     :   List[str]		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[int]	    =					[self.sep_token_id]
					_UpperCAmelCase						:				Optional[int]	    =					[self.cls_token_id]

					if token_ids_a is None:
							return len(cls + token_ids_a + sep       ) * [0]
					return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]




			@property
			def 							lowerCAmelCase__			(						self     :   List[Any]       )      ->List[str]:



					'''simple docstring'''







					return len(self.sp_model       )




			def 							lowerCAmelCase__			(						self     :   int       )      ->int:



					'''simple docstring'''







					_UpperCAmelCase						:				List[Any]	    =					{self.convert_ids_to_tokens(lowerCamelCase__       ): i for i in range(self.vocab_size       )}
					vocab.update(self.added_tokens_encoder       )
					return vocab




			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   str       )      ->List[str]:



					'''simple docstring'''







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




			def 							lowerCAmelCase__			(						self     :   Dict		,     lowerCamelCase__     :   Union[str, Any]       )      ->List[Any]:



					'''simple docstring'''







					if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
					_UpperCAmelCase						:				Optional[Any]	    =					self.sp_model.PieceToId(lowerCamelCase__       )

					return spm_id if spm_id else self.unk_token_id




			def 							lowerCAmelCase__			(						self     :   str		,     lowerCamelCase__     :   Any       )      ->Optional[Any]:



					'''simple docstring'''







					if index in self.fairseq_ids_to_tokens:
							return self.fairseq_ids_to_tokens[index]
					return self.sp_model.IdToPiece(lowerCamelCase__       )




			def 							lowerCAmelCase__			(						self     :   Any		,     lowerCamelCase__     :   List[Any]       )      ->Optional[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Union[str, Any]	    =					[]
					_UpperCAmelCase						:				Optional[Any]	    =					""
					_UpperCAmelCase						:				Optional[int]	    =					False
					for token in tokens:
							# make sure that special tokens are not decoded using sentencepiece model
							if token in self.all_special_tokens:
									if not prev_is_special:
											out_string += " "
									out_string += self.sp_model.decode(lowerCamelCase__       ) + token
									_UpperCAmelCase						:				Union[str, Any]	    =					True
									_UpperCAmelCase						:				Union[str, Any]	    =					[]
							else:
									current_sub_tokens.append(lowerCamelCase__       )
									_UpperCAmelCase						:				int	    =					False
					out_string += self.sp_model.decode(lowerCamelCase__       )
					return out_string.strip()




			def __getstate__(						self     :   Dict       )      ->List[Any]:



					'''simple docstring'''







					_UpperCAmelCase						:				List[str]	    =					self.__dict__.copy()
					_UpperCAmelCase						:				Optional[int]	    =					None
					return state




			def __setstate__(						self     :   Any		,     lowerCamelCase__     :   Dict       )      ->Tuple:



					'''simple docstring'''







					_UpperCAmelCase						:				Dict	    =					d

					# for backward compatibility
					if not hasattr(self		,     "sp_model_kwargs"       ):
							_UpperCAmelCase						:				List[Any]	    =					{}

					_UpperCAmelCase						:				Optional[int]	    =					spm.SentencePieceProcessor(**self.sp_model_kwargs       )
					self.sp_model.Load(self.vocab_file       )






			def 							lowerCAmelCase__			(						self     :   Optional[Any]		,     lowerCamelCase__     :   str		,     lowerCamelCase__     :   Optional[str] = None       )      ->Tuple[str]:



					'''simple docstring'''







					if not os.path.isdir(lowerCamelCase__       ):
							logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
							return
					_UpperCAmelCase						:				Union[str, Any]	    =					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						:				Dict	    =					self.sp_model.serialized_model_proto()
									fi.write(lowerCamelCase__       )

					return (out_vocab_file,)



