




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


__A						:		Any          =						["CoLA", "SST", "MRPC", "QQP", "STS", "MNLI", "SNLI", "QNLI", "RTE", "WNLI", "diagnostic"]
__A						:		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",
}

__A						:		str          =						"https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt"
__A						:		Optional[int]          =						"https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt"





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__   )     ->     Any:







				'''simple docstring'''


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





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__   )     ->     List[str]:







				'''simple docstring'''


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

				__lowerCAmelCase					=  []
				with open(os.path.join(UpperCamelCase__						,			"""dev_ids.tsv"""   )						,			encoding="""utf8"""   ) as ids_fh:
								for row in ids_fh:
												dev_ids.append(row.strip().split("""\t"""   )   )

				with open(UpperCamelCase__						,			encoding="""utf8"""   ) as data_fh, open(
				    os.path.join(UpperCamelCase__						,			"""train.tsv"""   )						,			"""w"""						,			encoding="""utf8"""   ) as train_fh, open(os.path.join(UpperCamelCase__						,			"""dev.tsv"""   )						,			"""w"""						,			encoding="""utf8"""   ) as dev_fh:
								__lowerCAmelCase					=  data_fh.readline()
								train_fh.write(UpperCamelCase__   )
								dev_fh.write(UpperCamelCase__   )
								for row in data_fh:
												__lowerCAmelCase	,				__lowerCAmelCase	,				__lowerCAmelCase	,				__lowerCAmelCase	,				__lowerCAmelCase					=  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(UpperCamelCase__						,			encoding="""utf8"""   ) as data_fh, open(
				    os.path.join(UpperCamelCase__						,			"""test.tsv"""   )						,			"""w"""						,			encoding="""utf8"""   ) as test_fh:
								__lowerCAmelCase					=  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(UpperCamelCase__   ):
												__lowerCAmelCase	,				__lowerCAmelCase	,				__lowerCAmelCase	,				__lowerCAmelCase	,				__lowerCAmelCase					=  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  (						UpperCamelCase__   )     ->     Dict:







				'''simple docstring'''


				print("""Downloading and extracting diagnostic..."""   )
				if not os.path.isdir(os.path.join(UpperCamelCase__						,			"""diagnostic"""   )   ):
								os.mkdir(os.path.join(UpperCamelCase__						,			"""diagnostic"""   )   )
				__lowerCAmelCase					=  os.path.join(UpperCamelCase__						,			"""diagnostic"""						,			"""diagnostic.tsv"""   )
				urllib.request.urlretrieve(TASKaPATH["""diagnostic"""]						,			UpperCamelCase__   )
				print("""\tCompleted!"""   )
				return





def      UpperCAmelCase  (						UpperCamelCase__   )     ->     Optional[int]:







				'''simple docstring'''


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





def      UpperCAmelCase  (						UpperCamelCase__   )     ->     str:







				'''simple docstring'''


				__lowerCAmelCase					=  argparse.ArgumentParser()
				parser.add_argument("""--data_dir"""						,			help="""directory to save data to"""						,			type=UpperCamelCase__						,			default="""glue_data"""   )
				parser.add_argument(
				    """--tasks"""						,			help="""tasks to download data for as a comma separated string"""						,			type=UpperCamelCase__						,			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=UpperCamelCase__						,			default=""""""						,			)
				__lowerCAmelCase					=  parser.parse_args(UpperCamelCase__   )

				if not os.path.isdir(args.data_dir   ):
								os.mkdir(args.data_dir   )
				__lowerCAmelCase					=  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(UpperCamelCase__						,			args.data_dir   )


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







"""simple docstring"""




import random
import shutil
import tempfile
import unittest

import numpy as np

from transformers import TaTokenizer, TaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torch
from transformers.utils.import_utils import is_speech_available, is_torch_available


if is_torch_available():
					pass

if is_speech_available():
					from transformers import EncodecFeatureExtractor, MusicgenProcessor


__lowerCAmelCase							:  Union[str, Any] 				=		random.Random()

def __snake_case (      UpperCamelCase						,					UpperCamelCase=1.0						,					UpperCamelCase=None						,					UpperCamelCase=None    )       ->    Tuple:


		"""simple docstring"""





		if rng is None:
				a__   		=     global_rng

		a__   		=     []
		for batch_idx in range(shape[0]    ):
				values.append([]    )
				for _ in range(shape[1]    ):
						values[-1].append(rng.random() * scale    )

		return values




@require_torch
@require_sentencepiece
class SCREAMING_SNAKE_CASE       (      unittest.TestCase					):






	'''simple docstring'''







	def    _UpperCamelCase							(  self :Optional[int]			)			->   List[str]:

			'''simple docstring'''






			a__   		=     '''facebook/musicgen-small'''
			a__   		=     tempfile.mkdtemp()


	def    _UpperCamelCase							(  self :Union[str, Any]       ,    **__magic_name__ :Union[str, Any]			)			->   str:

			'''simple docstring'''






			return TaTokenizer.from_pretrained(self.checkpoint       ,    **__magic_name__			)


	def    _UpperCamelCase							(  self :Optional[int]       ,    **__magic_name__ :Any			)			->   Optional[int]:

			'''simple docstring'''






			return EncodecFeatureExtractor.from_pretrained(self.checkpoint       ,    **__magic_name__			)


	def    _UpperCamelCase							(  self :Optional[int]			)			->   Optional[int]:

			'''simple docstring'''






			shutil.rmtree(self.tmpdirname			)


	def    _UpperCamelCase							(  self :Tuple			)			->   Any:

			'''simple docstring'''






			a__   		=     self.get_tokenizer()
			a__   		=     self.get_feature_extractor()

			a__   		=     MusicgenProcessor(tokenizer=__magic_name__       ,    feature_extractor=__magic_name__			)

			processor.save_pretrained(self.tmpdirname			)
			a__   		=     MusicgenProcessor.from_pretrained(self.tmpdirname			)

			self.assertEqual(processor.tokenizer.get_vocab()       ,    tokenizer.get_vocab()			)
			self.assertIsInstance(processor.tokenizer       ,    __magic_name__			)

			self.assertEqual(processor.feature_extractor.to_json_string()       ,    feature_extractor.to_json_string()			)
			self.assertIsInstance(processor.feature_extractor       ,    __magic_name__			)


	def    _UpperCamelCase							(  self :Dict			)			->   Optional[int]:

			'''simple docstring'''






			a__   		=     MusicgenProcessor(tokenizer=self.get_tokenizer()       ,    feature_extractor=self.get_feature_extractor()			)
			processor.save_pretrained(self.tmpdirname			)

			a__   		=     self.get_tokenizer(bos_token='''(BOS)'''       ,    eos_token='''(EOS)'''			)
			a__   		=     self.get_feature_extractor(do_normalize=__magic_name__       ,    padding_value=1.0			)

			a__   		=     MusicgenProcessor.from_pretrained(
			    self.tmpdirname       ,    bos_token='''(BOS)'''       ,    eos_token='''(EOS)'''       ,    do_normalize=__magic_name__       ,    padding_value=1.0			)

			self.assertEqual(processor.tokenizer.get_vocab()       ,    tokenizer_add_kwargs.get_vocab()			)
			self.assertIsInstance(processor.tokenizer       ,    __magic_name__			)

			self.assertEqual(processor.feature_extractor.to_json_string()       ,    feature_extractor_add_kwargs.to_json_string()			)
			self.assertIsInstance(processor.feature_extractor       ,    __magic_name__			)


	def    _UpperCamelCase							(  self :Any			)			->   Tuple:

			'''simple docstring'''






			a__   		=     self.get_feature_extractor()
			a__   		=     self.get_tokenizer()

			a__   		=     MusicgenProcessor(tokenizer=__magic_name__       ,    feature_extractor=__magic_name__			)

			a__   		=     floats_list((3, 1000)			)

			a__   		=     feature_extractor(__magic_name__       ,    return_tensors='''np'''			)
			a__   		=     processor(__magic_name__       ,    return_tensors='''np'''			)

			for key in input_feat_extract.keys():
					self.assertAlmostEqual(input_feat_extract[key].sum()       ,    input_processor[key].sum()       ,    delta=1e-2			)


	def    _UpperCamelCase							(  self :Tuple			)			->   Dict:

			'''simple docstring'''






			a__   		=     self.get_feature_extractor()
			a__   		=     self.get_tokenizer()

			a__   		=     MusicgenProcessor(tokenizer=__magic_name__       ,    feature_extractor=__magic_name__			)

			a__   		=     '''This is a test string'''

			a__   		=     processor(text=__magic_name__			)

			a__   		=     tokenizer(__magic_name__			)

			for key in encoded_tok.keys():
					self.assertListEqual(encoded_tok[key]       ,    encoded_processor[key]			)


	def    _UpperCamelCase							(  self :Tuple			)			->   Optional[Any]:

			'''simple docstring'''






			a__   		=     self.get_feature_extractor()
			a__   		=     self.get_tokenizer()

			a__   		=     MusicgenProcessor(tokenizer=__magic_name__       ,    feature_extractor=__magic_name__			)

			a__   		=     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

			a__   		=     processor.batch_decode(sequences=__magic_name__			)
			a__   		=     tokenizer.batch_decode(__magic_name__			)

			self.assertListEqual(__magic_name__       ,    __magic_name__			)


	def    _UpperCamelCase							(  self :Optional[Any]			)			->   int:

			'''simple docstring'''






			a__   		=     self.get_feature_extractor()
			a__   		=     self.get_tokenizer()

			a__   		=     MusicgenProcessor(tokenizer=__magic_name__       ,    feature_extractor=__magic_name__			)

			self.assertListEqual(
			    processor.model_input_names       ,    feature_extractor.model_input_names       ,    msg='''`processor` and `feature_extractor` model input names do not match'''       ,    )






	def    _UpperCamelCase							(  self :Any			)			->   List[str]:

			'''simple docstring'''






			a__   		=     self.get_feature_extractor(padding_side='''left'''			)
			a__   		=     self.get_tokenizer()

			a__   		=     MusicgenProcessor(tokenizer=__magic_name__       ,    feature_extractor=__magic_name__			)

			a__   		=     [floats_list((1, x)			)[0] for x in range(5       ,    20       ,    5			)]
			a__   		=     processor(__magic_name__			).padding_mask

			a__   		=     np.asarray(floats_list((3, 20)			)			)[:, None, :]
			a__   		=     processor.batch_decode(__magic_name__       ,    padding_mask=__magic_name__			)

			self.assertIsInstance(__magic_name__       ,    __magic_name__			)

			for audio in decoded_audios:
					self.assertIsInstance(__magic_name__       ,    np.ndarray			)

			self.assertTrue(decoded_audios[0].shape == (1, 10)			)
			self.assertTrue(decoded_audios[1].shape == (1, 15)			)
			self.assertTrue(decoded_audios[2].shape == (1, 20)			)




