
'''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_            =    "\\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 					a_					(datasets.GeneratorBasedBuilder      ):
       __lowerCAmelCase      :			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')
       __lowerCAmelCase      :			List[str]      = [
           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"""      ),
       ]

       __lowerCAmelCase      :			List[str]      = 'first_domain'  # It's not mandatory to have a default configuration. Just use one if it make sense.




       def 							__UpperCamelCase    (       self					):

         if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
           _lowerCAmelCase    :					Optional[int]							=   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"
           _lowerCAmelCase    :					str							=   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=snake_case_				,				homepage=_HOMEPAGE				,				license=_LICENSE				,				citation=_CITATION				,				)




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







       def 							__UpperCamelCase    (       self				,				snake_case_				,				snake_case_					):

         with open(snake_case_				,				encoding="""utf-8"""					) as f:
           for key, row in enumerate(snake_case_					):
             _lowerCAmelCase    :					Dict							=   json.loads(snake_case_					)
             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'''

import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand


def 		_UpperCAmelCase			(					_lowerCamelCase  :    List[Any]						)      ->  Optional[Any]:
  return EnvironmentCommand()



class 					a_					(_a      ):




       @staticmethod
       def 							__UpperCamelCase    (       snake_case_					):
         _lowerCAmelCase    :					Optional[Any]							=   parser.add_parser("""env"""				,				help="""Print relevant system environment info."""					)
         download_parser.set_defaults(func=snake_case_					)




       def 							__UpperCamelCase    (       self					):
         _lowerCAmelCase    :					Optional[Any]							=   {
             """`datasets` version""": version,
             """Platform""": platform.platform(),
             """Python version""": platform.python_version(),
             """Huggingface_hub version""": huggingface_hub.__version__,
             """PyArrow version""": pyarrow.__version__,
             """Pandas version""": pandas.__version__,
         }

         print("""\nCopy-and-paste the text below in your GitHub issue.\n"""					)
         print(self.format_dict(snake_case_					)					)

         return info







       @staticmethod
       def 							__UpperCamelCase    (       snake_case_					):
         return "\n".join([f'- {prop}: {val}' for prop, val in d.items()]					) + "\n"


