




'''simple docstring'''







import argparse
import os
import sys
import urllib.request
import zipfile


A			   =['CoLA', 'SST', 'MRPC', 'QQP', 'STS', 'MNLI', 'SNLI', 'QNLI', 'RTE', 'WNLI', 'diagnostic']
A			   ={
    'CoLA': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FCoLA.zip?alt=media&token=46d5e637-3411-4188-bc44-5809b5bfb5f4',
    'SST': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8',
    'MRPC': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2Fmrpc_dev_ids.tsv?alt=media&token=ec5c0836-31d5-48f4-b431-7480817f1adc',
    'QQP': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FQQP.zip?alt=media&token=700c6acf-160d-4d89-81d1-de4191d02cb5',
    'STS': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSTS-B.zip?alt=media&token=bddb94a7-8706-4e0d-a694-1109e12273b5',
    'MNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FMNLI.zip?alt=media&token=50329ea1-e339-40e2-809c-10c40afff3ce',
    'SNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSNLI.zip?alt=media&token=4afcfbb2-ff0c-4b2d-a09a-dbf07926f4df',
    'QNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FQNLIv2.zip?alt=media&token=6fdcf570-0fc5-4631-8456-9505272d1601',
    'RTE': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FRTE.zip?alt=media&token=5efa7e85-a0bb-4f19-8ea2-9e1840f077fb',
    'WNLI': 'https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FWNLI.zip?alt=media&token=068ad0a0-ded7-4bd7-99a5-5e00222e0faf',
    'diagnostic': 'https://storage.googleapis.com/mtl-sentence-representations.appspot.com/tsvsWithoutLabels%2FAX.tsv?GoogleAccessId=firebase-adminsdk-0khhl@mtl-sentence-representations.iam.gserviceaccount.com&Expires=2498860800&Signature=DuQ2CSPt2Yfre0C%2BiISrVYrIFaZH1Lc7hBVZDD4ZyR7fZYOMNOUGpi8QxBmTNOrNPjR3z1cggo7WXFfrgECP6FBJSsURv8Ybrue8Ypt%2FTPxbuJ0Xc2FhDi%2BarnecCBFO77RSbfuz%2Bs95hRrYhTnByqu3U%2FYZPaj3tZt5QdfpH2IUROY8LiBXoXS46LE%2FgOQc%2FKN%2BA9SoscRDYsnxHfG0IjXGwHN%2Bf88q6hOmAxeNPx6moDulUF6XMUAaXCSFU%2BnRO2RDL9CapWxj%2BDl7syNyHhB7987hZ80B%2FwFkQ3MEs8auvt5XW1%2Bd4aCU7ytgM69r8JDCwibfhZxpaa4gd50QXQ%3D%3D',
}

A			   ='https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt'
A			   ='https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt'





def 						snake_case_							(_a     :							str   ,       _a     :							int					):
    print(F"Downloading and extracting {task}..."					)
    UpperCAmelCase      	=		F"{task}.zip"
    urllib.request.urlretrieve(TASKaPATH[task]   ,       _a					)
    with zipfile.ZipFile(_a					) as zip_ref:
        zip_ref.extractall(_a					)
    os.remove(_a					)
    print('''\tCompleted!'''					)





def 						snake_case_							(_a     :							List[Any]   ,       _a     :							Dict					):
    print('''Processing MRPC...'''					)
    UpperCAmelCase      	=		os.path.join(_a   ,       '''MRPC'''					)
    if not os.path.isdir(_a					):
        os.mkdir(_a					)
    if path_to_data:
        UpperCAmelCase      	=		os.path.join(_a   ,       '''msr_paraphrase_train.txt'''					)
        UpperCAmelCase      	=		os.path.join(_a   ,       '''msr_paraphrase_test.txt'''					)
    else:
        print('''Local MRPC data not specified, downloading data from %s''' % MRPC_TRAIN					)
        UpperCAmelCase      	=		os.path.join(_a   ,       '''msr_paraphrase_train.txt'''					)
        UpperCAmelCase      	=		os.path.join(_a   ,       '''msr_paraphrase_test.txt'''					)
        urllib.request.urlretrieve(_a   ,       _a					)
        urllib.request.urlretrieve(_a   ,       _a					)
    if not os.path.isfile(_a					):
        raise ValueError(F"Train data not found at {mrpc_train_file}"					)
    if not os.path.isfile(_a					):
        raise ValueError(F"Test data not found at {mrpc_test_file}"					)
    urllib.request.urlretrieve(TASKaPATH['''MRPC''']   ,       os.path.join(_a   ,       '''dev_ids.tsv'''					)					)

    UpperCAmelCase      	=		[]
    with open(os.path.join(_a   ,       '''dev_ids.tsv'''					)   ,       encoding='''utf8'''					) as ids_fh:
        for row in ids_fh:
            dev_ids.append(row.strip().split('''\t'''					)					)

    with open(_a   ,       encoding='''utf8'''					) as data_fh, open(
        os.path.join(_a   ,       '''train.tsv'''					)   ,       '''w'''   ,       encoding='''utf8'''					) as train_fh, open(os.path.join(_a   ,       '''dev.tsv'''					)   ,       '''w'''   ,       encoding='''utf8'''					) as dev_fh:
        UpperCAmelCase      	=		data_fh.readline()
        train_fh.write(_a					)
        dev_fh.write(_a					)
        for row in data_fh:
            UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase      	=		row.strip().split('''\t'''					)
            if [ida, ida] in dev_ids:
                dev_fh.write('''%s\t%s\t%s\t%s\t%s\n''' % (label, ida, ida, sa, sa)					)
            else:
                train_fh.write('''%s\t%s\t%s\t%s\t%s\n''' % (label, ida, ida, sa, sa)					)

    with open(_a   ,       encoding='''utf8'''					) as data_fh, open(
        os.path.join(_a   ,       '''test.tsv'''					)   ,       '''w'''   ,       encoding='''utf8'''					) as test_fh:
        UpperCAmelCase      	=		data_fh.readline()
        test_fh.write('''index\t#1 ID\t#2 ID\t#1 String\t#2 String\n'''					)
        for idx, row in enumerate(_a					):
            UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase	,					UpperCAmelCase      	=		row.strip().split('''\t'''					)
            test_fh.write('''%d\t%s\t%s\t%s\t%s\n''' % (idx, ida, ida, sa, sa)					)
    print('''\tCompleted!'''					)





def 						snake_case_							(_a     :							Dict					):
    print('''Downloading and extracting diagnostic...'''					)
    if not os.path.isdir(os.path.join(_a   ,       '''diagnostic'''					)					):
        os.mkdir(os.path.join(_a   ,       '''diagnostic'''					)					)
    UpperCAmelCase      	=		os.path.join(_a   ,       '''diagnostic'''   ,       '''diagnostic.tsv'''					)
    urllib.request.urlretrieve(TASKaPATH['''diagnostic''']   ,       _a					)
    print('''\tCompleted!'''					)
    return





def 						snake_case_							(_a     :							Any					):
    UpperCAmelCase      	=		task_names.split(''','''					)
    if "all" in task_names:
        UpperCAmelCase      	=		TASKS
    else:
        UpperCAmelCase      	=		[]
        for task_name in task_names:
            if task_name not in TASKS:
                raise ValueError(F"Task {task_name} not found!"					)
            tasks.append(_a					)
    return tasks





def 						snake_case_							(_a     :							Dict					):
    UpperCAmelCase      	=		argparse.ArgumentParser()
    parser.add_argument('''--data_dir'''   ,       help='''directory to save data to'''   ,       type=_a   ,       default='''glue_data'''					)
    parser.add_argument(
        '''--tasks'''   ,       help='''tasks to download data for as a comma separated string'''   ,       type=_a   ,       default='''all'''					)
    parser.add_argument(
        '''--path_to_mrpc'''   ,       help='''path to directory containing extracted MRPC data, msr_paraphrase_train.txt and msr_paraphrase_text.txt'''   ,       type=_a   ,       default=''''''   ,       )
    UpperCAmelCase      	=		parser.parse_args(_a					)

    if not os.path.isdir(args.data_dir					):
        os.mkdir(args.data_dir					)
    UpperCAmelCase      	=		get_tasks(args.tasks					)

    for task in tasks:
        if task == "MRPC":
            format_mrpc(args.data_dir   ,       args.path_to_mrpc					)
        elif task == "diagnostic":
            download_diagnostic(args.data_dir					)
        else:
            download_and_extract(_a   ,       args.data_dir					)


if __name__ == "__main__":
      sys.exit(main(sys.argv[1:]))










'''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




