

from __future__ import annotations

from queue import Queue




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	tuple[int, int]:



    """simple docstring"""






    a ^= b
    b ^= a
    a ^= b
    return a, b




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	list[list[int]]:



    """simple docstring"""






    UpperCamelCase_      =	1
    while (1 << j) < max_node:
        for i in range(1 ,	max_node + 1 ):
            UpperCamelCase_      =	parent[j - 1][parent[j - 1][i]]
        j += 1
    return parent




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    if level[u] < level[v]:
        UpperCamelCase_      =	swap(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )
    # making depth of u same as depth of v
    for i in range(1_8 ,	-1 ,	-1 ):
        if level[u] - (1 << i) >= level[v]:
            UpperCamelCase_      =	parent[i][u]
    # at the same depth if u==v that mean lca is found
    if u == v:
        return u
    # moving both nodes upwards till lca in found
    for i in range(1_8 ,	-1 ,	-1 ):
        if parent[i][u] not in [0, parent[i][v]]:
            UpperCamelCase_      =	parent[i][u], parent[i][v]
    # returning longest common ancestor of u,v
    return parent[0][u]




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ = 1 ,	)->	tuple[list[int], list[list[int]]]:



    """simple docstring"""






    UpperCamelCase_      =	0
    UpperCamelCase_      =	Queue(maxsize=SCREAMING_SNAKE_CASE_ )
    q.put(SCREAMING_SNAKE_CASE_ )
    while q.qsize() != 0:
        UpperCamelCase_      =	q.get()
        for v in graph[u]:
            if level[v] == -1:
                UpperCamelCase_      =	level[u] + 1
                q.put(SCREAMING_SNAKE_CASE_ )
                UpperCamelCase_      =	u
    return level, parent




def  lowerCAmelCase(			)->	None:



    """simple docstring"""






    UpperCamelCase_      =	1_3
    # initializing with 0
    UpperCamelCase_      =	[[0 for _ in range(max_node + 1_0 )] for _ in range(2_0 )]
    # initializing with -1 which means every node is unvisited
    UpperCamelCase_      =	[-1 for _ in range(max_node + 1_0 )]
    UpperCamelCase_      =	{
        1: [2, 3, 4],
        2: [5],
        3: [6, 7],
        4: [8],
        5: [9, 1_0],
        6: [1_1],
        7: [],
        8: [1_2, 1_3],
        9: [],
        1_0: [],
        1_1: [],
        1_2: [],
        1_3: [],
    }
    UpperCamelCase_      =	breadth_first_search(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	1 )
    UpperCamelCase_      =	create_sparse(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )
    print("LCA of node 1 and 3 is: " ,	lowest_common_ancestor(1 ,	3 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ) )
    print("LCA of node 5 and 6 is: " ,	lowest_common_ancestor(5 ,	6 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ) )
    print("LCA of node 7 and 11 is: " ,	lowest_common_ancestor(7 ,	1_1 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ) )
    print("LCA of node 6 and 7 is: " ,	lowest_common_ancestor(6 ,	7 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ) )
    print("LCA of node 4 and 12 is: " ,	lowest_common_ancestor(4 ,	1_2 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ) )
    print("LCA of node 8 and 8 is: " ,	lowest_common_ancestor(8 ,	8 ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ) )


if __name__ == "__main__":
  main()



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


SCREAMING_SNAKE_CASE		:List[Any]				  =    ["""CoLA""", """SST""", """MRPC""", """QQP""", """STS""", """MNLI""", """SNLI""", """QNLI""", """RTE""", """WNLI""", """diagnostic"""]
SCREAMING_SNAKE_CASE		:List[Any]				  =    {
    """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""",
}

SCREAMING_SNAKE_CASE		:str				  =    """https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt"""
SCREAMING_SNAKE_CASE		:int				  =    """https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt"""




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	Tuple:



    """simple docstring"""






    print(f"Downloading and extracting {task}..." )
    UpperCamelCase_      =	f"{task}.zip"
    urllib.request.urlretrieve(TASKaPATH[task] ,	SCREAMING_SNAKE_CASE_ )
    with zipfile.ZipFile(SCREAMING_SNAKE_CASE_ ) as zip_ref:
        zip_ref.extractall(SCREAMING_SNAKE_CASE_ )
    os.remove(SCREAMING_SNAKE_CASE_ )
    print("\tCompleted!" )




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )->	Optional[Any]:



    """simple docstring"""






    print("Processing MRPC..." )
    UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"MRPC" )
    if not os.path.isdir(SCREAMING_SNAKE_CASE_ ):
        os.mkdir(SCREAMING_SNAKE_CASE_ )
    if path_to_data:
        UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"msr_paraphrase_train.txt" )
        UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"msr_paraphrase_test.txt" )
    else:
        print("Local MRPC data not specified, downloading data from %s" % MRPC_TRAIN )
        UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"msr_paraphrase_train.txt" )
        UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"msr_paraphrase_test.txt" )
        urllib.request.urlretrieve(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )
        urllib.request.urlretrieve(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ )
    if not os.path.isfile(SCREAMING_SNAKE_CASE_ ):
        raise ValueError(f"Train data not found at {mrpc_train_file}" )
    if not os.path.isfile(SCREAMING_SNAKE_CASE_ ):
        raise ValueError(f"Test data not found at {mrpc_test_file}" )
    urllib.request.urlretrieve(TASKaPATH["MRPC"] ,	os.path.join(SCREAMING_SNAKE_CASE_ ,	"dev_ids.tsv" ) )

    UpperCamelCase_      =	[]
    with open(os.path.join(SCREAMING_SNAKE_CASE_ ,	"dev_ids.tsv" ) ,	encoding="utf8" ) as ids_fh:
        for row in ids_fh:
            dev_ids.append(row.strip().split("\t" ) )

    with open(SCREAMING_SNAKE_CASE_ ,	encoding="utf8" ) as data_fh, open(
        os.path.join(SCREAMING_SNAKE_CASE_ ,	"train.tsv" ) ,	"w" ,	encoding="utf8" ) as train_fh, open(os.path.join(SCREAMING_SNAKE_CASE_ ,	"dev.tsv" ) ,	"w" ,	encoding="utf8" ) as dev_fh:
        UpperCamelCase_      =	data_fh.readline()
        train_fh.write(SCREAMING_SNAKE_CASE_ )
        dev_fh.write(SCREAMING_SNAKE_CASE_ )
        for row in data_fh:
            UpperCamelCase_     ,					UpperCamelCase_     ,					UpperCamelCase_     ,					UpperCamelCase_     ,					UpperCamelCase_      =	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(SCREAMING_SNAKE_CASE_ ,	encoding="utf8" ) as data_fh, open(
        os.path.join(SCREAMING_SNAKE_CASE_ ,	"test.tsv" ) ,	"w" ,	encoding="utf8" ) as test_fh:
        UpperCamelCase_      =	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(SCREAMING_SNAKE_CASE_ ):
            UpperCamelCase_     ,					UpperCamelCase_     ,					UpperCamelCase_     ,					UpperCamelCase_     ,					UpperCamelCase_      =	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  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	Tuple:



    """simple docstring"""






    print("Downloading and extracting diagnostic..." )
    if not os.path.isdir(os.path.join(SCREAMING_SNAKE_CASE_ ,	"diagnostic" ) ):
        os.mkdir(os.path.join(SCREAMING_SNAKE_CASE_ ,	"diagnostic" ) )
    UpperCamelCase_      =	os.path.join(SCREAMING_SNAKE_CASE_ ,	"diagnostic" ,	"diagnostic.tsv" )
    urllib.request.urlretrieve(TASKaPATH["diagnostic"] ,	SCREAMING_SNAKE_CASE_ )
    print("\tCompleted!" )
    return




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	Any:



    """simple docstring"""






    UpperCamelCase_      =	task_names.split("," )
    if "all" in task_names:
        UpperCamelCase_      =	TASKS
    else:
        UpperCamelCase_      =	[]
        for task_name in task_names:
            if task_name not in TASKS:
                raise ValueError(f"Task {task_name} not found!" )
            tasks.append(SCREAMING_SNAKE_CASE_ )
    return tasks




def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ )->	int:



    """simple docstring"""






    UpperCamelCase_      =	argparse.ArgumentParser()
    parser.add_argument("--data_dir" ,	help="directory to save data to" ,	type=SCREAMING_SNAKE_CASE_ ,	default="glue_data" )
    parser.add_argument(
        "--tasks" ,	help="tasks to download data for as a comma separated string" ,	type=SCREAMING_SNAKE_CASE_ ,	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=SCREAMING_SNAKE_CASE_ ,	default="" ,	)
    UpperCamelCase_      =	parser.parse_args(SCREAMING_SNAKE_CASE_ )

    if not os.path.isdir(args.data_dir ):
        os.mkdir(args.data_dir )
    UpperCamelCase_      =	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(SCREAMING_SNAKE_CASE_ ,	args.data_dir )


if __name__ == "__main__":
 sys.exit(main(sys.argv[1:]))
