

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


lowerCamelCase     =      ["""CoLA""", """SST""", """MRPC""", """QQP""", """STS""", """MNLI""", """SNLI""", """QNLI""", """RTE""", """WNLI""", """diagnostic"""]
lowerCamelCase     =      {
    """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""",
}

lowerCamelCase     =      """https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt"""
lowerCamelCase     =      """https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt"""




def     UpperCAmelCase__       (    _A   :				Union[str, Any]			,   _A   :				Tuple							):





  '''simple docstring'''







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




def     UpperCAmelCase__       (    _A   :				str			,   _A   :				str							):





  '''simple docstring'''







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

  a__						=[]
  with open(os.path.join(_A			,   '''dev_ids.tsv'''							)			,   encoding='''utf8'''							) as ids_fh:
    for row in ids_fh:
      dev_ids.append(row.strip().split('''\t'''							)							)

  with open(_A			,   encoding='''utf8'''							) as data_fh, open(
      os.path.join(_A			,   '''train.tsv'''							)			,   '''w'''			,   encoding='''utf8'''							) as train_fh, open(os.path.join(_A			,   '''dev.tsv'''							)			,   '''w'''			,   encoding='''utf8'''							) as dev_fh:
    a__						=data_fh.readline()
    train_fh.write(_A							)
    dev_fh.write(_A							)
    for row in data_fh:
      a__						=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(_A			,   encoding='''utf8'''							) as data_fh, open(
      os.path.join(_A			,   '''test.tsv'''							)			,   '''w'''			,   encoding='''utf8'''							) as test_fh:
    a__						=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(_A							):
      a__						=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     UpperCAmelCase__       (    _A   :				List[Any]							):





  '''simple docstring'''







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




def     UpperCAmelCase__       (    _A   :				int							):





  '''simple docstring'''







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




def     UpperCAmelCase__       (    _A   :				List[Any]							):





  '''simple docstring'''







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

  if not os.path.isdir(args.data_dir							):
    os.mkdir(args.data_dir							)
  a__						=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(_A			,   args.data_dir							)


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



from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available







@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class 		__magic_name__    (							lowerCamelCase__							):

   '''simple docstring'''




   lowerCamelCase__				:			Union[List[PIL.Image.Image], np.ndarray]
   lowerCamelCase__				:			Optional[List[bool]]


if is_transformers_available() and is_torch_available():
       from .modeling_roberta_series import RobertaSeriesModelWithTransformation
       from .pipeline_alt_diffusion import AltDiffusionPipeline
       from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline
