





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      ):



      """simple docstring"""






      UpperCAmelCase_  : str				      =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')
      UpperCAmelCase_  : int				      =[
          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"      ),
      ]

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







      def   UpperCAmelCase						(	self				)    ->				List[Any]:






        '''simple docstring'''






        if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
          __snake_case				:			List[str]            =    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"
          __snake_case				:			Union[str, Any]            =    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=UpperCAmelCase			,  homepage=_HOMEPAGE			,  license=_LICENSE			,  citation=_CITATION			,  )







      def   UpperCAmelCase						(	self			,  UpperCAmelCase				)    ->				Optional[Any]:






        '''simple docstring'''






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







      def   UpperCAmelCase						(	self			,  UpperCAmelCase			,  UpperCAmelCase				)    ->				Optional[int]:






        '''simple docstring'''






        with open(UpperCAmelCase			,  encoding="utf-8"				) as f:
          for key, row in enumerate(UpperCAmelCase				):
            __snake_case				:			Optional[int]            =    json.loads(UpperCAmelCase				)
            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"],
              }








import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


_UpperCamelCase    =	logging.get_logger(__name__)




class 			_lowerCamelCase	(      a      ):



      """simple docstring"""






      def __init__(	self			,  *UpperCAmelCase			,  **UpperCAmelCase				)    ->				None:






        '''simple docstring'''






        warnings.warn(
            "The class MaskFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
            " Please use MaskFormerImageProcessor instead."			,  UpperCAmelCase			,  )
        super().__init__(*UpperCAmelCase			,  **UpperCAmelCase				)

