

'''simple docstring'''

import csv
import json
import os

import datasets


# TODO: Add BibTeX citation
# Find for instance the citation on arxiv or on the dataset repo/website
UpperCAmelCase							=					'''\
@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
}
'''

# TODO: Add description of the dataset here
# You can copy an official description
UpperCAmelCase							=					'''\
This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
'''

# TODO: Add a link to an official homepage for the dataset here
UpperCAmelCase							=					''''''

# TODO: Add the licence for the dataset here if you can find it
UpperCAmelCase							=					''''''

# TODO: Add link to the official dataset URLs here
# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
UpperCAmelCase							=					{
    '''first_domain''': '''https://huggingface.co/great-new-dataset-first_domain.zip''',
    '''second_domain''': '''https://huggingface.co/great-new-dataset-second_domain.zip''',
}


class 					lowerCAmelCase							( datasets.GeneratorBasedBuilder				):
       lowerCAmelCase_				=	datasets.Version("1.1.0"				)

       # This is an example of a dataset with multiple configurations.
       # If you don't want/need to define several sub-sets in your dataset,
       # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.

       # If you need to make complex sub-parts in the datasets with configurable options
       # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
       # BUILDER_CONFIG_CLASS = MyBuilderConfig

       # You will be able to load one or the other configurations in the following list with
       # data = datasets.load_dataset('my_dataset', 'first_domain')
       # data = datasets.load_dataset('my_dataset', 'second_domain')
       lowerCAmelCase_				=	[
           datasets.BuilderConfig(name="first_domain"				,     version=A				,     description="This part of my dataset covers a first domain"				),
           datasets.BuilderConfig(name="second_domain"				,     version=A				,     description="This part of my dataset covers a second domain"				),
       ]

       lowerCAmelCase_				=	"first_domain"  # It's not mandatory to have a default configuration. Just use one if it make sense.







       def      snake_case				(							self     :	Optional[Any] ):







            """simple docstring"""







            if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
                 __lowercase     						=datasets.Features(
                     {
                         'sentence': datasets.Value('string' ),
                         'option1': datasets.Value('string' ),
                         'answer': datasets.Value('string' )
                         # These are the features of your dataset like images, labels ...
                     } )
            else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
                 __lowercase     						=datasets.Features(
                     {
                         'sentence': datasets.Value('string' ),
                         'option2': datasets.Value('string' ),
                         'second_domain_answer': datasets.Value('string' )
                         # These are the features of your dataset like images, labels ...
                     } )
            return datasets.DatasetInfo(
                # This is the description that will appear on the datasets page.
                description=_DESCRIPTION  , features=__lowercase  , homepage=_HOMEPAGE  , license=_LICENSE  , citation=_CITATION  , )







       def      snake_case				(							self     :	Optional[int]  , __lowercase     :	List[str] ):







            """simple docstring"""







            __lowercase     						=_URLS[self.config.name]
            __lowercase     						=dl_manager.download_and_extract(__lowercase )
            return [
                datasets.SplitGenerator(
                    name=datasets.Split.TRAIN  , gen_kwargs={
                        'filepath': os.path.join(__lowercase  , 'train.jsonl' ),
                        'split': 'train',
                    }  , ),
                datasets.SplitGenerator(
                    name=datasets.Split.VALIDATION  , gen_kwargs={
                        'filepath': os.path.join(__lowercase  , 'dev.jsonl' ),
                        'split': 'dev',
                    }  , ),
                datasets.SplitGenerator(
                    name=datasets.Split.TEST  , gen_kwargs={
                        'filepath': os.path.join(__lowercase  , 'test.jsonl' ),
                        'split': 'test'
                    }  , ),
            ]







       def      snake_case				(							self     :	Tuple  , __lowercase     :	List[str]  , __lowercase     :	List[Any] ):







            """simple docstring"""







            with open(__lowercase  , encoding='utf-8' ) as f:
                 for key, row in enumerate(__lowercase ):
                      __lowercase     						=json.loads(__lowercase )
                      if self.config.name == "first_domain":
                           # Yields examples as (key, example) tuples
                           yield key, {
                               "sentence": data["sentence"],
                               "option1": data["option1"],
                               "answer": "" if split == "test" else data["answer"],
                           }
                      else:
                           yield key, {
                               "sentence": data["sentence"],
                               "option2": data["option2"],
                               "second_domain_answer": "" if split == "test" else data["second_domain_answer"],
                           }





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase							=					{
    '''configuration_videomae''': ['''VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VideoMAEConfig'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					[
           '''VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''VideoMAEForPreTraining''',
           '''VideoMAEModel''',
           '''VideoMAEPreTrainedModel''',
           '''VideoMAEForVideoClassification''',
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					['''VideoMAEFeatureExtractor''']
       UpperCAmelCase							=					['''VideoMAEImageProcessor''']

if TYPE_CHECKING:
       from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_videomae import (
                  VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  VideoMAEForPreTraining,
                  VideoMAEForVideoClassification,
                  VideoMAEModel,
                  VideoMAEPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_videomae import VideoMAEFeatureExtractor
              from .image_processing_videomae import VideoMAEImageProcessor

else:
       import sys

       UpperCAmelCase							=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


