Fixed W4ngatang/download_glue_data.py script to download GLUE data

download_glue_data.py

''' 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 (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, 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":'https://dl.fbaipublicfiles.com/glue/data/CoLA.zip',
             "SST":'https://dl.fbaipublicfiles.com/glue/data/SST-2.zip',
             "QQP":'https://dl.fbaipublicfiles.com/glue/data/STS-B.zip',
             "STS":'https://dl.fbaipublicfiles.com/glue/data/QQP-clean.zip',
             "MNLI":'https://dl.fbaipublicfiles.com/glue/data/MNLI.zip',
             "QNLI":'https://dl.fbaipublicfiles.com/glue/data/QNLIv2.zip',
             "RTE":'https://dl.fbaipublicfiles.com/glue/data/RTE.zip',
             "WNLI":'https://dl.fbaipublicfiles.com/glue/data/WNLI.zip',
             "diagnostic":'https://dl.fbaipublicfiles.com/glue/data/AX.tsv',
             "MRPC": "https://raw.githubusercontent.com/MegEngine/Models/master/official/nlp/bert/glue_data/MRPC/dev_ids.tsv"}

MRPC_TRAIN = 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt'
MRPC_TEST = 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt'

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 = "%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:
        try:
            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")
            return
    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 io.open(mrpc_test_file, encoding='utf-8') as data_fh, \
            io.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))

    try:
        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.")
        return

    dev_ids = []
    with io.open(os.path.join(mrpc_dir, "dev_ids.tsv"), encoding='utf-8') as ids_fh:
        for row in ids_fh:
            dev_ids.append(row.strip().split('\t'))

    with io.open(mrpc_train_file, encoding='utf-8') as data_fh, \
         io.open(os.path.join(mrpc_dir, "train.tsv"), 'w', encoding='utf-8') as train_fh, \
         io.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))
                
    print("\tCompleted!")
    
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)
    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('--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):
        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:]))

Thank you!

Thank you..

Thank you!

thank you !!!

Thank U!

How can I solve the following errors?
Traceback (most recent call last):
File "E:\Project\16 Large language model development\01 bert-master\download_glue_data.py", line 153, in
sys.exit(main(sys.argv[1:]))
File "E:\Project\16 Large language model development\01 bert-master\download_glue_data.py", line 149, in main
download_and_extract(task, args.data_dir)
File "E:\Project\16 Large language model development\01 bert-master\download_glue_data.py", line 50, in download_and_extract
urllib.request.urlretrieve(TASK2PATH[task], data_file)
File "E:\SoftWareInstall\02 anacondainstall\lib\urllib\request.py", line 278, in urlretrieve
raise ContentTooShortError(
urllib.error.ContentTooShortError: <urlopen error retrieval incomplete: got only 7192576 out of 7439277 bytes>

Sorry，May I ask where you encountered this problem, it seems that I don't quite understand。 Or how did you find me?&nbsp; 临界丶 ***@***.*** &nbsp;

…

------------------&nbsp;原始邮件&nbsp;------------------ 发件人: ***@***.***&gt;; 发送时间: 2023年4月11日(星期二) 下午5:21 收件人: ***@***.***&gt;; 抄送: ***@***.***&gt;; 主题: Re: vlasenkoalexey/download_glue_data.py @zhangyong123ZY commented on this gist. How can I solve the following errors? Traceback (most recent call last): File "E:\Project\16 Large language model development\01 bert-master\download_glue_data.py", line 153, in sys.exit(main(sys.argv[1:])) File "E:\Project\16 Large language model development\01 bert-master\download_glue_data.py", line 149, in main download_and_extract(task, args.data_dir) File "E:\Project\16 Large language model development\01 bert-master\download_glue_data.py", line 50, in download_and_extract urllib.request.urlretrieve(TASK2PATH[task], data_file) File "E:\SoftWareInstall\02 anacondainstall\lib\urllib\request.py", line 278, in urlretrieve raise ContentTooShortError( urllib.error.ContentTooShortError: <urlopen error retrieval incomplete: got only 7192576 out of 7439277 bytes&gt; — Reply to this email directly, view it on GitHub or unsubscribe. You are receiving this email because you commented on the thread. Triage notifications on the go with GitHub Mobile for iOS or Android. &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;

Thank you!

Thank you!

thank you so much!!

thank you so much!!

Thank you !!!