



'''simple docstring'''



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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_barthez import BarthezTokenizer
else:
		lowerCamelCase	 =       None

lowerCamelCase	 =       logging.get_logger(__name__)

lowerCamelCase	 =       {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

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"""
        ),
    },
    """tokenizer_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json"""
        ),
    },
}

lowerCamelCase	 =       {
    """moussaKam/mbarthez""": 1024,
    """moussaKam/barthez""": 1024,
    """moussaKam/barthez-orangesum-title""": 1024,
}

lowerCamelCase	 =       """▁"""





class _UpperCamelCase		(     _lowerCAmelCase		):





				'''simple docstring'''





				lowerCAmelCase__					    =    VOCAB_FILES_NAMES
				lowerCAmelCase__					    =    PRETRAINED_VOCAB_FILES_MAP
				lowerCAmelCase__					    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCAmelCase__					    =    ['input_ids', 'attention_mask']
				lowerCAmelCase__					    =    BarthezTokenizer

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







											'''simple docstring'''

											__lowercase       	=AddedToken(_lowerCAmelCase  ,       lstrip=_lowerCAmelCase  ,       rstrip=_lowerCAmelCase) if isinstance(_lowerCAmelCase  ,       _lowerCAmelCase) else mask_token

											super().__init__(
											    _lowerCAmelCase  ,       tokenizer_file=_lowerCAmelCase  ,       bos_token=_lowerCAmelCase  ,       eos_token=_lowerCAmelCase  ,       unk_token=_lowerCAmelCase  ,       sep_token=_lowerCAmelCase  ,       cls_token=_lowerCAmelCase  ,       pad_token=_lowerCAmelCase  ,       mask_token=_lowerCAmelCase  ,       **_lowerCAmelCase  ,       )

											__lowercase       	=vocab_file
											__lowercase       	=False if not self.vocab_file else True

				def 				__lowerCamelCase     (							self  :  str  ,       _lowerCAmelCase  :  List[int]  ,       _lowerCAmelCase  :  Optional[List[int]] = None):







											'''simple docstring'''

											if token_ids_a is None:
																		return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
											__lowercase       	=[self.cls_token_id]
											__lowercase       	=[self.sep_token_id]
											return cls + token_ids_a + sep + sep + token_ids_a + sep

				def 				__lowerCamelCase     (							self  :  Optional[Any]  ,       _lowerCAmelCase  :  List[int]  ,       _lowerCAmelCase  :  Optional[List[int]] = None):







											'''simple docstring'''

											__lowercase       	=[self.sep_token_id]
											__lowercase       	=[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]

				def 				__lowerCamelCase     (							self  :  List[Any]  ,       _lowerCAmelCase  :  str  ,       _lowerCAmelCase  :  Optional[str] = None):







											'''simple docstring'''

											if not self.can_save_slow_tokenizer:
																		raise ValueError(
																		    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
																		    'tokenizer.')

											if not os.path.isdir(_lowerCAmelCase):
																		logger.error(f"""Vocabulary path ({save_directory}) should be a directory""")
																		return
											__lowercase       	=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):
																		copyfile(self.vocab_file  ,       _lowerCAmelCase)

											return (out_vocab_file,)








'''simple docstring'''



import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict



@pytest.mark.parametrize(
    'files'  ,   [
        ['full:README.md', 'dataset_infos.json'],
        ['empty:README.md', 'dataset_infos.json'],
        ['dataset_infos.json'],
        ['full:README.md'],
    ]  ,   )
def   _A       (   _lowerCAmelCase  ,   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=tmp_path_factory.mktemp('dset_infos_dir'					)
							if "full:README.md" in files:
														with open(dataset_infos_dir / 'README.md'  ,   'w'					) as f:
																					f.write('---\ndataset_info:\n  dataset_size: 42\n---'					)
							if "empty:README.md" in files:
														with open(dataset_infos_dir / 'README.md'  ,   'w'					) as f:
																					f.write(''					)
    # we want to support dataset_infos.json for backward compatibility
							if "dataset_infos.json" in files:
														with open(dataset_infos_dir / 'dataset_infos.json'  ,   'w'					) as f:
																					f.write('{"default": {"dataset_size": 42}}'					)
							__lowercase       	=DatasetInfosDict.from_directory(_lowerCAmelCase					)
							assert dataset_infos
							assert dataset_infos["default"].dataset_size == 42



@pytest.mark.parametrize(
    'dataset_info'  ,   [
        DatasetInfo(),
        DatasetInfo(
            description='foo'  ,   features=Features({'a': Value('int32'					)}					)  ,   builder_name='builder'  ,   config_name='config'  ,   version='1.0.0'  ,   splits=[{'name': 'train'}]  ,   download_size=42  ,   ),
    ]  ,   )
def   _A       (   _lowerCAmelCase  ,   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=str(_lowerCAmelCase					)
							dataset_info.write_to_directory(_lowerCAmelCase					)
							__lowercase       	=DatasetInfo.from_directory(_lowerCAmelCase					)
							assert dataset_info == reloaded
							assert os.path.exists(os.path.join(_lowerCAmelCase  ,   'dataset_info.json'					)					)



def   _A       (   ):



							"""simple docstring"""



							__lowercase       	=DatasetInfo(
							    description='foo'  ,   citation='bar'  ,   homepage='https://foo.bar'  ,   license='CC0'  ,   features=Features({'a': Value('int32'					)}					)  ,   post_processed={}  ,   supervised_keys=()  ,   task_templates=[]  ,   builder_name='builder'  ,   config_name='config'  ,   version='1.0.0'  ,   splits=[{'name': 'train', 'num_examples': 42}]  ,   download_checksums={}  ,   download_size=1_337  ,   post_processing_size=442  ,   dataset_size=1_234  ,   size_in_bytes=1_337 + 442 + 1_234  ,   )
							__lowercase       	=dataset_info._to_yaml_dict()
							assert sorted(_lowerCAmelCase					) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML					)
							for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
														assert key in dataset_info_yaml_dict
														assert isinstance(dataset_info_yaml_dict[key]  ,   (list, dict, int, str)					)
							__lowercase       	=yaml.safe_dump(_lowerCAmelCase					)
							__lowercase       	=yaml.safe_load(_lowerCAmelCase					)
							assert dataset_info_yaml_dict == reloaded



def   _A       (   ):



							"""simple docstring"""



							__lowercase       	=DatasetInfo()
							__lowercase       	=dataset_info._to_yaml_dict()
							assert dataset_info_yaml_dict == {}



@pytest.mark.parametrize(
    'dataset_infos_dict'  ,   [
        DatasetInfosDict(),
        DatasetInfosDict({'default': DatasetInfo()}					),
        DatasetInfosDict({'my_config_name': DatasetInfo()}					),
        DatasetInfosDict(
            {
                'default': DatasetInfo(
                    description='foo'  ,   features=Features({'a': Value('int32'					)}					)  ,   builder_name='builder'  ,   config_name='config'  ,   version='1.0.0'  ,   splits=[{'name': 'train'}]  ,   download_size=42  ,   )
            }					),
        DatasetInfosDict(
            {
                'v1': DatasetInfo(dataset_size=42					),
                'v2': DatasetInfo(dataset_size=1_337					),
            }					),
    ]  ,   )
def   _A       (   _lowerCAmelCase  ,   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=str(_lowerCAmelCase					)
							dataset_infos_dict.write_to_directory(_lowerCAmelCase					)
							__lowercase       	=DatasetInfosDict.from_directory(_lowerCAmelCase					)

							# the config_name of the dataset_infos_dict take over the attribute
							for config_name, dataset_info in dataset_infos_dict.items():
														__lowercase       	=config_name
														# the yaml representation doesn't include fields like description or citation
														# so we just test that we can recover what we can from the yaml
														__lowercase       	=DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()					)
							assert dataset_infos_dict == reloaded

							if dataset_infos_dict:
														assert os.path.exists(os.path.join(_lowerCAmelCase  ,   'README.md'					)					)



