首先是demo
bert裏README.md裏給出下載GLUE DATA腳本download_glue_data.py已經404了
先把這個代碼貼出來（我運行網上找的download_glue_data.py文件 報錯 一個‘UnicodeDecodeError: 'gbk' codec can't decode byte 0x9d in position 680: illegal multibyte sequence’錯誤，所以找到了這個，對文件讀取有utf-8的處理）
''' Script for downloading all GLUE data.
Example usage:
python download_glue_data.py --data_dir data --tasks all
Note: for legal reasons, we are unable to host MRPC ourselves.
By default, we use the version hosted by the SentEval team, which is already tokenized. If that becomes unavailable,
you can download the original data from (https://download.microsoft.com/download/D/4/6/D46FF87A-F6B9-4252-AA8B-3604ED519838/MSRParaphraseCorpus.msi) and extract the data from it manually.
For Windows users, you can run the .msi file. For Mac and Linux users, you'll need an external library like 'cabextract' (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
'''
import os
import sys
import shutil
import argparse
import tempfile
import urllib.request
import zipfile
TASKS = ["CoLA", "SST", "MRPC", "QQP", "STS", "MNLI", "SNLI", "QNLI", "RTE", "WNLI", "diagnostic"]
TASK2PATH = {
"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%2FQNLI.zip?alt=media&token=c24cad61-f2df-4f04-9ab6-aa576fa829d0',
"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'}
MRPC_TRAIN = 'https://s3.amazonaws.com/senteval/senteval_data/msr_paraphrase_train.txt'
MRPC_TEST = 'https://s3.amazonaws.com/senteval/senteval_data/msr_paraphrase_test.txt'
def download_and_extract(task, data_dir):
print("Downloading and extracting %s..." % task)
data_file = "%s.zip" % task
urllib.request.urlretrieve(TASK2PATH[task], data_file)
with zipfile.ZipFile(data_file) as zip_ref:
zip_ref.extractall(data_dir)
os.remove(data_file)
print("\tCompleted!")
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):
os.mkdir(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")
else:
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)
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
#urllib.request.urlretrieve(TASK2PATH["MRPC"], os.path.join(mrpc_dir, "dev_ids.tsv"))
dev_ids = []
with open(os.path.join(mrpc_dir, "dev_ids.tsv")) as ids_fh:
for row in ids_fh:
dev_ids.append(row.strip().split('\t'))
with open(mrpc_train_file, encoding='utf-8') as data_fh, \
open(os.path.join(mrpc_dir, "train.tsv"), 'w', encoding='utf-8') as train_fh, \
open(os.path.join(mrpc_dir, "dev.tsv"), 'w', encoding='utf-8') as dev_fh:
header = data_fh.readline()
train_fh.write(header)
dev_fh.write(header)
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))
else:
train_fh.write("%s\t%s\t%s\t%s\t%s\n" % (label, id1, id2, s1, s2))
with open(mrpc_test_file, encoding='utf-8') as data_fh, \
open(os.path.join(mrpc_dir, "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))
print("\tCompleted!")
def download_diagnostic(data_dir):
print("Downloading and extracting diagnostic...")
if not os.path.isdir(os.path.join(data_dir, "MNLI")):
os.mkdir(os.path.join(data_dir, "MNLI"))
data_file = os.path.join(data_dir, "MNLI", "diagnostic.tsv")
urllib.request.urlretrieve(TASK2PATH["diagnostic"], data_file)
print("\tCompleted!")
return
def get_tasks(task_names):
task_names = task_names.split(',')
if "all" in task_names:
tasks = TASKS
else:
tasks = []
for task_name in task_names:
assert task_name in TASKS, "Task %s not found!" % task_name
tasks.append(task_name)
return tasks
def main(arguments):
parser = argparse.ArgumentParser()
parser.add_argument(
'-d',
'--data_dir',
help='directory to save data to',
type=str,
default='../glue_data')
parser.add_argument(
'-t',
'--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):
os.mkdir(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_diagnostic(args.data_dir)
else:
download_and_extract(task, args.data_dir)
if __name__ == '__main__':
sys.exit(main(sys.argv[1:]))