




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


_lowerCamelCase					:     str					  =  ["CoLA", "SST", "MRPC", "QQP", "STS", "MNLI", "SNLI", "QNLI", "RTE", "WNLI", "diagnostic"]
_lowerCamelCase					:     str					  =  {
    "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					:     int					  =  "https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt"
_lowerCamelCase					:     str					  =  "https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt"




def 							_UpperCAmelCase     (UpperCamelCase_       :       str					,			UpperCamelCase_       :       Any				):
				'''simple docstring'''
				print(F"Downloading and extracting {task}..."				)
				_lowerCAmelCase			:			Dict        =					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_       :       int					,			UpperCamelCase_       :       Union[str, Any]				):
				'''simple docstring'''
				print("""Processing MRPC..."""				)
				_lowerCAmelCase			:			Any        =					os.path.join(UpperCamelCase_					,			"""MRPC"""				)
				if not os.path.isdir(UpperCamelCase_				):
								os.mkdir(UpperCamelCase_				)
				if path_to_data:
								_lowerCAmelCase			:			int        =					os.path.join(UpperCamelCase_					,			"""msr_paraphrase_train.txt"""				)
								_lowerCAmelCase			:			Union[str, Any]        =					os.path.join(UpperCamelCase_					,			"""msr_paraphrase_test.txt"""				)
				else:
								print("""Local MRPC data not specified, downloading data from %s""" % MRPC_TRAIN				)
								_lowerCAmelCase			:			Dict        =					os.path.join(UpperCamelCase_					,			"""msr_paraphrase_train.txt"""				)
								_lowerCAmelCase			:			Tuple        =					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			:			Dict        =					[]
				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			:			Optional[Any]        =					data_fh.readline()
								train_fh.write(UpperCamelCase_				)
								dev_fh.write(UpperCamelCase_				)
								for row in data_fh:
												_lowerCAmelCase    ,			_lowerCAmelCase    ,			_lowerCAmelCase    ,			_lowerCAmelCase    ,			_lowerCAmelCase			:			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(UpperCamelCase_					,			encoding="""utf8"""				) as data_fh, open(
				    os.path.join(UpperCamelCase_					,			"""test.tsv"""				)					,			"""w"""					,			encoding="""utf8"""				) as test_fh:
								_lowerCAmelCase			:			Any        =					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			:			int        =					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_       :       Any				):
				'''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			:			Optional[Any]        =					os.path.join(UpperCamelCase_					,			"""diagnostic"""					,			"""diagnostic.tsv"""				)
				urllib.request.urlretrieve(TASKaPATH["""diagnostic"""]					,			UpperCamelCase_				)
				print("""\tCompleted!"""				)
				return




def 							_UpperCAmelCase     (UpperCamelCase_       :       Optional[int]				):
				'''simple docstring'''
				_lowerCAmelCase			:			List[Any]        =					task_names.split(""","""				)
				if "all" in task_names:
								_lowerCAmelCase			:			int        =					TASKS
				else:
								_lowerCAmelCase			:			List[str]        =					[]
								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_       :       Optional[int]				):
				'''simple docstring'''
				_lowerCAmelCase			:			str        =					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			:			Dict        =					parser.parse_args(UpperCamelCase_				)

				if not os.path.isdir(args.data_dir				):
								os.mkdir(args.data_dir				)
				_lowerCAmelCase			:			List[Any]        =					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:]))







import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


_lowerCamelCase					:     Optional[Any]					  =  logging.get_logger(__name__)

_lowerCamelCase					:     Dict					  =  {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

_lowerCamelCase					:     List[str]					  =  {
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "allenai/longformer-base-4096": (
            "https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
    },
}

_lowerCamelCase					:     Dict					  =  {
    "allenai/longformer-base-4096": 4_0_9_6,
    "allenai/longformer-large-4096": 4_0_9_6,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4_0_9_6,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4_0_9_6,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4_0_9_6,
}
class 				__snake_case     (_a						):
				lowerCAmelCase__			=   VOCAB_FILES_NAMES
				lowerCAmelCase__			=   PRETRAINED_VOCAB_FILES_MAP
				lowerCAmelCase__			=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCAmelCase__			=   ["input_ids", "attention_mask"]
				lowerCAmelCase__			=   LongformerTokenizer



				def __init__(					self					:						Optional[Any]						,		_UpperCAmelCase					:						Tuple=None						,		_UpperCAmelCase					:						List[str]=None						,		_UpperCAmelCase					:						List[str]=None						,		_UpperCAmelCase					:						Union[str, Any]="replace"						,		_UpperCAmelCase					:						str="<s>"						,		_UpperCAmelCase					:						str="</s>"						,		_UpperCAmelCase					:						int="</s>"						,		_UpperCAmelCase					:						str="<s>"						,		_UpperCAmelCase					:						Optional[Any]="<unk>"						,		_UpperCAmelCase					:						Optional[Any]="<pad>"						,		_UpperCAmelCase					:						Any="<mask>"						,		_UpperCAmelCase					:						Optional[int]=False						,		_UpperCAmelCase					:						List[str]=True						,		**_UpperCAmelCase					:						Optional[int]						,		)     ->			str:





								'''simple docstring'''




								super().__init__(
								    _UpperCAmelCase						,		_UpperCAmelCase						,		tokenizer_file=_UpperCAmelCase						,		errors=_UpperCAmelCase						,		bos_token=_UpperCAmelCase						,		eos_token=_UpperCAmelCase						,		sep_token=_UpperCAmelCase						,		cls_token=_UpperCAmelCase						,		unk_token=_UpperCAmelCase						,		pad_token=_UpperCAmelCase						,		mask_token=_UpperCAmelCase						,		add_prefix_space=_UpperCAmelCase						,		trim_offsets=_UpperCAmelCase						,		**_UpperCAmelCase						,		)

								_lowerCAmelCase			:			Tuple        =					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()					)
								if pre_tok_state.get("""add_prefix_space"""						,		_UpperCAmelCase					) != add_prefix_space:
												_lowerCAmelCase			:			str        =					getattr(_UpperCAmelCase						,		pre_tok_state.pop("""type"""					)					)
												_lowerCAmelCase			:			Dict        =					add_prefix_space
												_lowerCAmelCase			:			Union[str, Any]        =					pre_tok_class(**_UpperCAmelCase					)

								_lowerCAmelCase			:			List[Any]        =					add_prefix_space

								_lowerCAmelCase			:			List[str]        =					"""post_processor"""
								_lowerCAmelCase			:			str        =					getattr(self.backend_tokenizer						,		_UpperCAmelCase						,		_UpperCAmelCase					)
								if tokenizer_component_instance:
												_lowerCAmelCase			:			Any        =					json.loads(tokenizer_component_instance.__getstate__()					)

												# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
												if "sep" in state:
																_lowerCAmelCase			:			str        =					tuple(state["""sep"""]					)
												if "cls" in state:
																_lowerCAmelCase			:			int        =					tuple(state["""cls"""]					)

												_lowerCAmelCase			:			Any        =					False

												if state.get("""add_prefix_space"""						,		_UpperCAmelCase					) != add_prefix_space:
																_lowerCAmelCase			:			int        =					add_prefix_space
																_lowerCAmelCase			:			List[str]        =					True

												if state.get("""trim_offsets"""						,		_UpperCAmelCase					) != trim_offsets:
																_lowerCAmelCase			:			List[str]        =					trim_offsets
																_lowerCAmelCase			:			List[str]        =					True

												if changes_to_apply:
																_lowerCAmelCase			:			List[str]        =					getattr(_UpperCAmelCase						,		state.pop("""type"""					)					)
																_lowerCAmelCase			:			Any        =					component_class(**_UpperCAmelCase					)
																setattr(self.backend_tokenizer						,		_UpperCAmelCase						,		_UpperCAmelCase					)



				@property
				def 					SCREAMING_SNAKE_CASE				(					self					:						List[Any]					)     ->			str:





								'''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 					SCREAMING_SNAKE_CASE				(					self					:						Any						,		_UpperCAmelCase					:						Any					)     ->			Tuple:





								'''simple docstring'''




								_lowerCAmelCase			:			Tuple        =					AddedToken(_UpperCAmelCase						,		lstrip=_UpperCAmelCase						,		rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase						,		_UpperCAmelCase					) else value
								_lowerCAmelCase			:			List[Any]        =					value



				def 					SCREAMING_SNAKE_CASE				(					self					:						int						,		*_UpperCAmelCase					:						str						,		**_UpperCAmelCase					:						Union[str, Any]					)     ->			BatchEncoding:





								'''simple docstring'''




								_lowerCAmelCase			:			Dict        =					kwargs.get("""is_split_into_words"""						,		_UpperCAmelCase					)
								assert self.add_prefix_space or not is_split_into_words, (
								    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
								    "to use it with pretokenized inputs."
								)

								return super()._batch_encode_plus(*_UpperCAmelCase						,		**_UpperCAmelCase					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						str						,		*_UpperCAmelCase					:						Any						,		**_UpperCAmelCase					:						Optional[Any]					)     ->			BatchEncoding:





								'''simple docstring'''




								_lowerCAmelCase			:			Any        =					kwargs.get("""is_split_into_words"""						,		_UpperCAmelCase					)

								assert self.add_prefix_space or not is_split_into_words, (
								    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
								    "to use it with pretokenized inputs."
								)

								return super()._encode_plus(*_UpperCAmelCase						,		**_UpperCAmelCase					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Dict						,		_UpperCAmelCase					:						str						,		_UpperCAmelCase					:						Optional[str] = None					)     ->			Tuple[str]:





								'''simple docstring'''




								_lowerCAmelCase			:			int        =					self._tokenizer.model.save(_UpperCAmelCase						,		name=_UpperCAmelCase					)
								return tuple(_UpperCAmelCase					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Any						,		_UpperCAmelCase					:						Any						,		_UpperCAmelCase					:						str=None					)     ->			List[Any]:





								'''simple docstring'''




								_lowerCAmelCase			:			Any        =					[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 					SCREAMING_SNAKE_CASE				(					self					:						List[Any]						,		_UpperCAmelCase					:						List[int]						,		_UpperCAmelCase					:						Optional[List[int]] = None					)     ->			List[int]:





								'''simple docstring'''




								_lowerCAmelCase			:			Dict        =					[self.sep_token_id]
								_lowerCAmelCase			:			Optional[Any]        =					[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]

