


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


__lowerCAmelCase     :			Tuple      =['CoLA', 'SST', 'MRPC', 'QQP', 'STS', 'MNLI', 'SNLI', 'QNLI', 'RTE', 'WNLI', 'diagnostic']
__lowerCAmelCase     :			Tuple      ={
    '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',
}

__lowerCAmelCase     :			List[str]      ='https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt'
__lowerCAmelCase     :			int      ='https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt'


def 	_UpperCamelCase							(				lowercase__   ,	lowercase__				):
						print(F'''Downloading and extracting {task}...'''				)
						__SCREAMING_SNAKE_CASE						:					List[str]		      =		F'''{task}.zip'''
						urllib.request.urlretrieve(TASKaPATH[task]   ,	lowercase__				)
						with zipfile.ZipFile(lowercase__				) as zip_ref:
												zip_ref.extractall(lowercase__				)
						os.remove(lowercase__				)
						print('''\tCompleted!'''				)


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

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

						with open(lowercase__   ,	encoding='''utf8'''				) as data_fh, open(
						    os.path.join(lowercase__   ,	'''train.tsv'''				)   ,	'''w'''   ,	encoding='''utf8'''				) as train_fh, open(os.path.join(lowercase__   ,	'''dev.tsv'''				)   ,	'''w'''   ,	encoding='''utf8'''				) as dev_fh:
												__SCREAMING_SNAKE_CASE						:					Optional[int]		      =		data_fh.readline()
												train_fh.write(lowercase__				)
												dev_fh.write(lowercase__				)
												for row in data_fh:
																		__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE						:					Optional[int]		      =		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(lowercase__   ,	encoding='''utf8'''				) as data_fh, open(
						    os.path.join(lowercase__   ,	'''test.tsv'''				)   ,	'''w'''   ,	encoding='''utf8'''				) as test_fh:
												__SCREAMING_SNAKE_CASE						:					List[str]		      =		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(lowercase__				):
																		__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE						:					Any		      =		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 	_UpperCamelCase							(				lowercase__				):
						print('''Downloading and extracting diagnostic...'''				)
						if not os.path.isdir(os.path.join(lowercase__   ,	'''diagnostic'''				)				):
												os.mkdir(os.path.join(lowercase__   ,	'''diagnostic'''				)				)
						__SCREAMING_SNAKE_CASE						:					Optional[Any]		      =		os.path.join(lowercase__   ,	'''diagnostic'''   ,	'''diagnostic.tsv'''				)
						urllib.request.urlretrieve(TASKaPATH['''diagnostic''']   ,	lowercase__				)
						print('''\tCompleted!'''				)
						return


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


def 	_UpperCamelCase							(				lowercase__				):
						__SCREAMING_SNAKE_CASE						:					Dict		      =		argparse.ArgumentParser()
						parser.add_argument('''--data_dir'''   ,	help='''directory to save data to'''   ,	type=lowercase__   ,	default='''glue_data'''				)
						parser.add_argument(
						    '''--tasks'''   ,	help='''tasks to download data for as a comma separated string'''   ,	type=lowercase__   ,	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=lowercase__   ,	default=''''''   ,	)
						__SCREAMING_SNAKE_CASE						:					Any		      =		parser.parse_args(lowercase__				)

						if not os.path.isdir(args.data_dir				):
												os.mkdir(args.data_dir				)
						__SCREAMING_SNAKE_CASE						:					Tuple		      =		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(lowercase__   ,	args.data_dir				)


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




from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
						from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore
class 	_lowercase				(      A__	):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__    :      int      =		c_float


				@property
				def 		__magic_name__(	self      :int     )		->      int:
										return sizeof(self.value     )




def 	_UpperCamelCase							(				lowercase__   ,	lowercase__   ,	lowercase__ = 0				):
						# < 0 is possible if using a dynamic axis
						if dimension <= 0:
												__SCREAMING_SNAKE_CASE						:					int		      =		fixed_dimension

						dimension -= num_token_to_add
						return dimension


def 	_UpperCamelCase							(				lowercase__   ,	lowercase__				):
						return num_parameters * dtype.size


def 	_UpperCamelCase							(				lowercase__				):
						from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

						try:
												return AutoProcessor.from_pretrained(lowercase__				)
						except (ValueError, OSError, KeyError):
												__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE						:					Tuple		      =		None, None
												try:
																		__SCREAMING_SNAKE_CASE						:					List[Any]		      =		AutoTokenizer.from_pretrained(lowercase__				)
												except (OSError, KeyError):
																		pass
												try:
																		__SCREAMING_SNAKE_CASE						:					Optional[int]		      =		AutoFeatureExtractor.from_pretrained(lowercase__				)
												except (OSError, KeyError):
																		pass

												if tokenizer is not None and feature_extractor is not None:
																		raise ValueError(
																		    F'''Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor.'''				)
												elif tokenizer is None and feature_extractor is None:
																		return None
												elif tokenizer is not None:
																		return tokenizer
												else:
																		return feature_extractor
