




'''simple docstring'''







import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


A			   =logging.get_logger(__name__)

A			   ={'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

A			   ={
    'vocab_file': {
        'microsoft/mpnet-base': 'https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt',
    },
    'tokenizer_file': {
        'microsoft/mpnet-base': 'https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json',
    },
}

A			   ={
    'microsoft/mpnet-base': 5_12,
}

A			   ={
    'microsoft/mpnet-base': {'do_lower_case': True},
}


class       _a  (     __a			):
       __a    :					int           = VOCAB_FILES_NAMES
       __a    :					str           = PRETRAINED_VOCAB_FILES_MAP
       __a    :					Dict           = PRETRAINED_INIT_CONFIGURATION
       __a    :					Union[str, Any]           = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __a    :					Optional[Any]           = MPNetTokenizer
       __a    :					List[str]           = ["""input_ids""", """attention_mask"""]
       def __init__(     self						:     List[str]       ,    lowercase						:     List[Any]=None       ,    lowercase						:     List[Any]=None       ,    lowercase						:     Any=True       ,    lowercase						:     str="<s>"       ,    lowercase						:     Any="</s>"       ,    lowercase						:     Tuple="</s>"       ,    lowercase						:     int="<s>"       ,    lowercase						:     Optional[Any]="[UNK]"       ,    lowercase						:     Union[str, Any]="<pad>"       ,    lowercase						:     Optional[int]="<mask>"       ,    lowercase						:     Optional[int]=True       ,    lowercase						:     Optional[Any]=None       ,    **lowercase						:     Union[str, Any]       ,    ):



           '''simple docstring'''

           super().__init__(
               lowercase       ,    tokenizer_file=lowercase       ,    do_lower_case=lowercase       ,    bos_token=lowercase       ,    eos_token=lowercase       ,    sep_token=lowercase       ,    cls_token=lowercase       ,    unk_token=lowercase       ,    pad_token=lowercase       ,    mask_token=lowercase       ,    tokenize_chinese_chars=lowercase       ,    strip_accents=lowercase       ,    **lowercase       ,    )

           UpperCAmelCase      	=		json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
           if (
               pre_tok_state.get('''lowercase'''       ,    lowercase    ) != do_lower_case
               or pre_tok_state.get('''strip_accents'''       ,    lowercase    ) != strip_accents
           ):
               UpperCAmelCase      	=		getattr(lowercase       ,    pre_tok_state.pop('''type'''    )    )
               UpperCAmelCase      	=		do_lower_case
               UpperCAmelCase      	=		strip_accents
               UpperCAmelCase      	=		pre_tok_class(**lowercase    )

           UpperCAmelCase      	=		do_lower_case
       @property
       def    A				(     self						:     Union[str, Any]    ):



           '''simple docstring'''

           if self._mask_token is None:
               if self.verbose:
                   logger.error('''Using mask_token, but it is not set yet.'''    )
               return None
           return str(self._mask_token    )
       @mask_token.setter
       def    A				(     self						:     int       ,    lowercase						:     Dict    ):



           '''simple docstring'''

           UpperCAmelCase      	=		AddedToken(lowercase       ,    lstrip=lowercase       ,    rstrip=lowercase    ) if isinstance(lowercase       ,    lowercase    ) else value
           UpperCAmelCase      	=		value
       def    A				(     self						:     Tuple       ,    lowercase						:     Dict       ,    lowercase						:     Optional[Any]=None    ):



           '''simple docstring'''

           UpperCAmelCase      	=		[self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
               return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]
       def    A				(     self						:     Dict       ,    lowercase						:     List[int]       ,    lowercase						:     Optional[List[int]] = None    ):



           '''simple docstring'''

           UpperCAmelCase      	=		[self.sep_token_id]
           UpperCAmelCase      	=		[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    A				(     self						:     Union[str, Any]       ,    lowercase						:     str       ,    lowercase						:     Optional[str] = None    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self._tokenizer.model.save(lowercase       ,    name=lowercase    )
           return tuple(lowercase    )










'''simple docstring'''







import multiprocessing
import os
from typing import BinaryIO, Optional, Union

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader


class       _a  (     __a			):
       def __init__(     self						:     Any       ,    lowercase						:     NestedDataStructureLike[PathLike]       ,    lowercase						:     Optional[NamedSplit] = None       ,    lowercase						:     Optional[Features] = None       ,    lowercase						:     str = None       ,    lowercase						:     bool = False       ,    lowercase						:     bool = False       ,    lowercase						:     Optional[int] = None       ,    **lowercase						:     str       ,    ):



           '''simple docstring'''

           super().__init__(
               lowercase       ,    split=lowercase       ,    features=lowercase       ,    cache_dir=lowercase       ,    keep_in_memory=lowercase       ,    streaming=lowercase       ,    num_proc=lowercase       ,    **lowercase       ,    )
           UpperCAmelCase      	=		path_or_paths if isinstance(lowercase       ,    lowercase    ) else {self.split: path_or_paths}
           UpperCAmelCase      	=		Csv(
               cache_dir=lowercase       ,    data_files=lowercase       ,    features=lowercase       ,    **lowercase       ,    )







       def    A				(     self						:     Tuple    ):



           '''simple docstring'''

           if self.streaming:
               UpperCAmelCase      	=		self.builder.as_streaming_dataset(split=self.split    )
           # Build regular (map-style) dataset
           else:
               UpperCAmelCase      	=		None
               UpperCAmelCase      	=		None
               UpperCAmelCase      	=		None
               UpperCAmelCase      	=		None

               self.builder.download_and_prepare(
                   download_config=lowercase       ,    download_mode=lowercase       ,    verification_mode=lowercase       ,    base_path=lowercase       ,    num_proc=self.num_proc       ,    )
               UpperCAmelCase      	=		self.builder.as_dataset(
                   split=self.split       ,    verification_mode=lowercase       ,    in_memory=self.keep_in_memory    )
           return dataset






class       _a  :
       def __init__(     self						:     Optional[int]       ,    lowercase						:     Dataset       ,    lowercase						:     Union[PathLike, BinaryIO]       ,    lowercase						:     Optional[int] = None       ,    lowercase						:     Optional[int] = None       ,    **lowercase						:     int       ,    ):



           '''simple docstring'''

           if num_proc is not None and num_proc <= 0:
               raise ValueError(f"num_proc {num_proc} must be an integer > 0."    )

           UpperCAmelCase      	=		dataset
           UpperCAmelCase      	=		path_or_buf
           UpperCAmelCase      	=		batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
           UpperCAmelCase      	=		num_proc
           UpperCAmelCase      	=		'''utf-8'''
           UpperCAmelCase      	=		to_csv_kwargs
       def    A				(     self						:     Union[str, Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.to_csv_kwargs.pop('''path_or_buf'''       ,    lowercase    )
           UpperCAmelCase      	=		self.to_csv_kwargs.pop('''header'''       ,    lowercase    )
           UpperCAmelCase      	=		self.to_csv_kwargs.pop('''index'''       ,    lowercase    )

           if isinstance(self.path_or_buf       ,    (str, bytes, os.PathLike)    ):
               with open(self.path_or_buf       ,    '''wb+'''    ) as buffer:
                   UpperCAmelCase      	=		self._write(file_obj=lowercase       ,    header=lowercase       ,    index=lowercase       ,    **self.to_csv_kwargs    )
           else:
               UpperCAmelCase      	=		self._write(file_obj=self.path_or_buf       ,    header=lowercase       ,    index=lowercase       ,    **self.to_csv_kwargs    )
           return written
       def    A				(     self						:     List[str]       ,    lowercase						:     Dict    ):



           '''simple docstring'''

           UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase      	=		args

           UpperCAmelCase      	=		query_table(
               table=self.dataset.data       ,    key=slice(lowercase       ,    offset + self.batch_size    )       ,    indices=self.dataset._indices       ,    )
           UpperCAmelCase      	=		batch.to_pandas().to_csv(
               path_or_buf=lowercase       ,    header=header if (offset == 0) else False       ,    index=lowercase       ,    **lowercase    )
           return csv_str.encode(self.encoding    )







       def    A				(     self						:     List[str]       ,    lowercase						:     BinaryIO       ,    lowercase						:     int       ,    lowercase						:     List[str]       ,    **lowercase						:     List[Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		0

           if self.num_proc is None or self.num_proc == 1:
               for offset in logging.tqdm(
                   range(0       ,    len(self.dataset    )       ,    self.batch_size    )       ,    unit='''ba'''       ,    disable=not logging.is_progress_bar_enabled()       ,    desc='''Creating CSV from Arrow format'''       ,    ):
                   UpperCAmelCase      	=		self._batch_csv((offset, header, index, to_csv_kwargs)    )
                   written += file_obj.write(lowercase    )

           else:
               UpperCAmelCase	,					UpperCAmelCase      	=		len(self.dataset    ), self.batch_size
               with multiprocessing.Pool(self.num_proc    ) as pool:
                   for csv_str in logging.tqdm(
                       pool.imap(
                           self._batch_csv       ,    [(offset, header, index, to_csv_kwargs) for offset in range(0       ,    lowercase       ,    lowercase    )]       ,    )       ,    total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size       ,    unit='''ba'''       ,    disable=not logging.is_progress_bar_enabled()       ,    desc='''Creating CSV from Arrow format'''       ,    ):
                       written += file_obj.write(lowercase    )

           return written




