
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   						=     "\\n@InProceedings{huggingface:dataset,\ntitle = {A great new dataset},\nauthor={huggingface, Inc.\n},\nyear={2020}\n}\n"

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

# 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 				UpperCamelCase__		(	datasets.GeneratorBasedBuilder	):






       """simple docstring"""


       UpperCAmelCase_				       =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_				       =[
           datasets.BuilderConfig(name="first_domain"       ,    version=__SCREAMING_SNAKE_CASE       ,    description="This part of my dataset covers a first domain"	),
           datasets.BuilderConfig(name="second_domain"       ,    version=__SCREAMING_SNAKE_CASE       ,    description="This part of my dataset covers a second domain"	),
       ]

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



       def     _UpperCamelCase	(							self	)				->				Any:
          # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
          if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
             SCREAMING_SNAKE_CASE_	=      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"
             SCREAMING_SNAKE_CASE_	=      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=_A ,     homepage=_HOMEPAGE ,     license=_LICENSE ,     citation=_CITATION ,     )



       def     _UpperCamelCase	(							self ,     _A	)				->				Tuple:
          # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
          # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name

          # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
          # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
          # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
          SCREAMING_SNAKE_CASE_	=      _URLS[self.config.name]
          SCREAMING_SNAKE_CASE_	=      dl_manager.download_and_extract(_A	)
          return [
              datasets.SplitGenerator(
                  name=datasets.Split.TRAIN ,     gen_kwargs={
                      '''filepath''': os.path.join(_A ,     '''train.jsonl'''	),
                      '''split''': '''train''',
                  } ,     ),
              datasets.SplitGenerator(
                  name=datasets.Split.VALIDATION ,     gen_kwargs={
                      '''filepath''': os.path.join(_A ,     '''dev.jsonl'''	),
                      '''split''': '''dev''',
                  } ,     ),
              datasets.SplitGenerator(
                  name=datasets.Split.TEST ,     gen_kwargs={
                      '''filepath''': os.path.join(_A ,     '''test.jsonl'''	),
                      '''split''': '''test'''
                  } ,     ),
          ]




       def     _UpperCamelCase	(							self ,     _A ,     _A	)				->				Any:
          # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
          # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
          with open(_A ,     encoding='''utf-8'''	) as f:
             for key, row in enumerate(_A	):
                SCREAMING_SNAKE_CASE_	=      json.loads(_A	)
                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"],
                   }




from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


__UpperCAmelCase   						=     datasets.utils.logging.get_logger(__name__)





class 				UpperCamelCase__		(	folder_based_builder.FolderBasedBuilderConfig	):






       """simple docstring"""


       UpperCAmelCase_				       =None
       UpperCAmelCase_				       =None







class 				UpperCamelCase__		(	folder_based_builder.FolderBasedBuilder	):






       """simple docstring"""


       UpperCAmelCase_				       =datasets.Image()
       UpperCAmelCase_				       ="image"
       UpperCAmelCase_				       =ImageFolderConfig
       UpperCAmelCase_				       =42  # definition at the bottom of the script
       UpperCAmelCase_				       =ImageClassification(image_column="image"       ,    label_column="label"	)







__UpperCAmelCase   						=     [
    ".blp",
    ".bmp",
    ".dib",
    ".bufr",
    ".cur",
    ".pcx",
    ".dcx",
    ".dds",
    ".ps",
    ".eps",
    ".fit",
    ".fits",
    ".fli",
    ".flc",
    ".ftc",
    ".ftu",
    ".gbr",
    ".gif",
    ".grib",
    ".h5",
    ".hdf",
    ".png",
    ".apng",
    ".jp2",
    ".j2k",
    ".jpc",
    ".jpf",
    ".jpx",
    ".j2c",
    ".icns",
    ".ico",
    ".im",
    ".iim",
    ".tif",
    ".tiff",
    ".jfif",
    ".jpe",
    ".jpg",
    ".jpeg",
    ".mpg",
    ".mpeg",
    ".msp",
    ".pcd",
    ".pxr",
    ".pbm",
    ".pgm",
    ".ppm",
    ".pnm",
    ".psd",
    ".bw",
    ".rgb",
    ".rgba",
    ".sgi",
    ".ras",
    ".tga",
    ".icb",
    ".vda",
    ".vst",
    ".webp",
    ".wmf",
    ".emf",
    ".xbm",
    ".xpm",
]
__UpperCAmelCase   						=     IMAGE_EXTENSIONS


