# What does this PR do?

[Sorry for the spams, GitHub had some issues]

Same as #24075, but that PR got freezed after I force pushed (after rebase), and my changes to address the comments were not able to appear)

(amy have already approved #24075)

----

Byebye!

EOL of python 3.7 is `2023/06/27`.

https://endoflife.date/python
⚠️ Time to say goodbye to py37. # What does this PR do?

[Sorry for the spams, GitHub had some issues]

Same as #24075, but that PR got freezed after I force pushed (after rebase), and my changes to address the comments were not able to appear)

(amy have already approved #24075)

----

Byebye!

EOL of python 3.7 is `2023/06/27`.

https://endoflife.date/python
""" Script for downloading all GLUE data.
Original source: https://gist.github.com/W4ngatang/60c2bdb54d156a41194446737ce03e2e

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 argparse
import os
import sys
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%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",
}

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(f"Downloading and extracting {task}...")
    data_file = f"{task}.zip"
    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:
        print("Local MRPC data not specified, downloading data from %s" % MRPC_TRAIN)
        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)
    if not os.path.isfile(mrpc_train_file):
        raise ValueError(f"Train data not found at {mrpc_train_file}")
    if not os.path.isfile(mrpc_test_file):
        raise ValueError(f"Test data not found at {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"), encoding="utf8") as ids_fh:
        for row in ids_fh:
            dev_ids.append(row.strip().split("\t"))

    with open(mrpc_train_file, encoding="utf8") as data_fh, open(
        os.path.join(mrpc_dir, "train.tsv"), "w", encoding="utf8"
    ) as train_fh, open(os.path.join(mrpc_dir, "dev.tsv"), "w", encoding="utf8") 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="utf8") as data_fh, open(
        os.path.join(mrpc_dir, "test.tsv"), "w", encoding="utf8"
    ) 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, "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:
            if task_name not in TASKS:
                raise ValueError(f"Task {task_name} not found!")
            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:]))

""" Script for downloading all GLUE data.
Original source: https://gist.github.com/W4ngatang/60c2bdb54d156a41194446737ce03e2e

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 argparse
import os
import sys
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%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",
}

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(f"Downloading and extracting {task}...")
    data_file = f"{task}.zip"
    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:
        print("Local MRPC data not specified, downloading data from %s" % MRPC_TRAIN)
        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)
    if not os.path.isfile(mrpc_train_file):
        raise ValueError(f"Train data not found at {mrpc_train_file}")
    if not os.path.isfile(mrpc_test_file):
        raise ValueError(f"Test data not found at {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"), encoding="utf8") as ids_fh:
        for row in ids_fh:
            dev_ids.append(row.strip().split("\t"))

    with open(mrpc_train_file, encoding="utf8") as data_fh, open(
        os.path.join(mrpc_dir, "train.tsv"), "w", encoding="utf8"
    ) as train_fh, open(os.path.join(mrpc_dir, "dev.tsv"), "w", encoding="utf8") 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="utf8") as data_fh, open(
        os.path.join(mrpc_dir, "test.tsv"), "w", encoding="utf8"
    ) 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, "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:
            if task_name not in TASKS:
                raise ValueError(f"Task {task_name} not found!")
            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:]))
