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Created May 19, 2021 22:44
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Fixed W4ngatang/ script to download GLUE data
''' Script for downloading all GLUE data.
Note: for legal reasons, we are unable to host MRPC.
You can either use the version hosted by the SentEval team, which is already tokenized,
or you can download the original data from ( and extract the data from it manually.
For Windows users, you can run the .msi file. For Mac and Linux users, consider an external library such as 'cabextract' (see below for an example).
You should then rename and place specific files in a folder (see below for an example).
mkdir MRPC
cabextract MSRParaphraseCorpus.msi -d MRPC
cat MRPC/_2DEC3DBE877E4DB192D17C0256E90F1D | tr -d $'\r' > MRPC/msr_paraphrase_train.txt
cat MRPC/_D7B391F9EAFF4B1B8BCE8F21B20B1B61 | tr -d $'\r' > MRPC/msr_paraphrase_test.txt
rm MRPC/_*
rm MSRParaphraseCorpus.msi
1/30/19: It looks like SentEval is no longer hosting their extracted and tokenized MRPC data, so you'll need to download the data from the original source for now.
2/11/19: It looks like SentEval actually *is* hosting the extracted data. Hooray!
import io
import os
import sys
import shutil
import argparse
import tempfile
import urllib
import urllib.request
import zipfile
TASKS = ["CoLA", "SST", "MRPC", "QQP", "STS", "MNLI", "QNLI", "RTE", "WNLI", "diagnostic", "MRPC"]
TASK2PATH = {"CoLA":'',
"MRPC": ""}
def download_and_extract(task, data_dir):
print("Downloading and extracting %s..." % task)
if task == "MNLI":
print("\tNote (12/10/20): This script no longer downloads SNLI. You will need to manually download and format the data to use SNLI.")
data_file = "" % task
urllib.request.urlretrieve(TASK2PATH[task], data_file)
with zipfile.ZipFile(data_file) as zip_ref:
def format_mrpc(data_dir, path_to_data):
print("Processing MRPC...")
mrpc_dir = os.path.join(data_dir, "MRPC")
if not os.path.isdir(mrpc_dir):
if path_to_data:
mrpc_train_file = os.path.join(path_to_data, "msr_paraphrase_train.txt")
mrpc_test_file = os.path.join(path_to_data, "msr_paraphrase_test.txt")
mrpc_train_file = os.path.join(mrpc_dir, "msr_paraphrase_train.txt")
mrpc_test_file = os.path.join(mrpc_dir, "msr_paraphrase_test.txt")
urllib.request.urlretrieve(MRPC_TRAIN, mrpc_train_file)
urllib.request.urlretrieve(MRPC_TEST, mrpc_test_file)
except urllib.error.HTTPError:
print("Error downloading MRPC")
assert os.path.isfile(mrpc_train_file), "Train data not found at %s" % mrpc_train_file
assert os.path.isfile(mrpc_test_file), "Test data not found at %s" % mrpc_test_file
with, encoding='utf-8') as data_fh, \, "test.tsv"), 'w', encoding='utf-8') as test_fh:
header = 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(data_fh):
label, id1, id2, s1, s2 = row.strip().split('\t')
test_fh.write("%d\t%s\t%s\t%s\t%s\n" % (idx, id1, id2, s1, s2))
urllib.request.urlretrieve(TASK2PATH["MRPC"], os.path.join(mrpc_dir, "dev_ids.tsv"))
except KeyError or urllib.error.HTTPError:
print("\tError downloading standard development IDs for MRPC. You will need to manually split your data.")
dev_ids = []
with, "dev_ids.tsv"), encoding='utf-8') as ids_fh:
for row in ids_fh:
with, encoding='utf-8') as data_fh, \, "train.tsv"), 'w', encoding='utf-8') as train_fh, \, "dev.tsv"), 'w', encoding='utf-8') as dev_fh:
header = data_fh.readline()
for row in data_fh:
label, id1, id2, s1, s2 = row.strip().split('\t')
if [id1, id2] in dev_ids:
dev_fh.write("%s\t%s\t%s\t%s\t%s\n" % (label, id1, id2, s1, s2))
train_fh.write("%s\t%s\t%s\t%s\t%s\n" % (label, id1, id2, s1, s2))
def download_diagnostic(data_dir):
print("Downloading and extracting diagnostic...")
if not os.path.isdir(os.path.join(data_dir, "diagnostic")):
os.mkdir(os.path.join(data_dir, "diagnostic"))
data_file = os.path.join(data_dir, "diagnostic", "diagnostic.tsv")
urllib.request.urlretrieve(TASK2PATH["diagnostic"], data_file)
def get_tasks(task_names):
task_names = task_names.split(',')
if "all" in task_names:
tasks = TASKS
tasks = []
for task_name in task_names:
assert task_name in TASKS, "Task %s not found!" % task_name
return tasks
def main(arguments):
parser = argparse.ArgumentParser()
parser.add_argument('--data_dir', help='directory to save data to', type=str, default='glue_data')
parser.add_argument('--tasks', help='tasks to download data for as a comma separated string',
type=str, 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=str, default='')
args = parser.parse_args(arguments)
if not os.path.isdir(args.data_dir):
tasks = get_tasks(args.tasks)
for task in tasks:
if task == 'MRPC':
format_mrpc(args.data_dir, args.path_to_mrpc)
elif task == 'diagnostic':
download_and_extract(task, args.data_dir)
if __name__ == '__main__':
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wsh3776 commented Sep 26, 2021

Thank you!

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Thank you..

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Thank you!

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Hollylhh commented Jun 2, 2022

thank you !!!

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OOOlsen commented Sep 6, 2022

Thank U!

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How can I solve the following errors?
Traceback (most recent call last):
File "E:\Project\16 Large language model development\01 bert-master\", line 153, in
File "E:\Project\16 Large language model development\01 bert-master\", line 149, in main
download_and_extract(task, args.data_dir)
File "E:\Project\16 Large language model development\01 bert-master\", line 50, in download_and_extract
urllib.request.urlretrieve(TASK2PATH[task], data_file)
File "E:\SoftWareInstall\02 anacondainstall\lib\urllib\", line 278, in urlretrieve
raise ContentTooShortError(
urllib.error.ContentTooShortError: <urlopen error retrieval incomplete: got only 7192576 out of 7439277 bytes>

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OOOlsen commented Apr 11, 2023 via email

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Elfsong commented May 13, 2023

Thank you!

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Thank you!

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thank you so much!!

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thank you so much!!

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NoisyGone commented Dec 20, 2023

Thank you !!!

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