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
lowerCAmelCase      :				Optional[int]     			='''\
@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
lowerCAmelCase      :				List[str]     			='''\
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
lowerCAmelCase      :				int     			=''''''

# TODO: Add the licence for the dataset here if you can find it
lowerCAmelCase      :				Optional[Any]     			=''''''

# 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)
lowerCAmelCase      :				Tuple     			={
    '''first_domain''': '''https://huggingface.co/great-new-dataset-first_domain.zip''',
    '''second_domain''': '''https://huggingface.co/great-new-dataset-second_domain.zip''',
}




class 						__snake_case						(			datasets.GeneratorBasedBuilder		):





      '''simple docstring'''






      _snake_case     		=							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')
      _snake_case     		=							[
          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'		),
      ]

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



      def 						_SCREAMING_SNAKE_CASE     (       self  :					Union[str, Any])					->Dict:


          """simple docstring"""


          if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
              _lowerCamelCase  :		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  :		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 						_SCREAMING_SNAKE_CASE     (       self  :					str     ,	_UpperCamelCase  :					Optional[Any])					->List[str]:


          """simple docstring"""


          _lowerCamelCase  :		List[str]			    =    _URLS[self.config.name]
          _lowerCamelCase  :		Optional[int]			    =    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 						_SCREAMING_SNAKE_CASE     (       self  :					List[Any]     ,	_UpperCamelCase  :					Any     ,	_UpperCamelCase  :					Optional[Any])					->int:


          """simple docstring"""


          with open(UpperCamelCase_     ,	encoding="""utf-8""") as f:
              for key, row in enumerate(UpperCamelCase_):
                  _lowerCamelCase  :		List[Any]			    =    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"],
                      }








"""simple docstring"""





from collections.abc import Callable

snake_case__		:  Optional[int]     					=					Callable[[float], float]  # type alias for a real -> real function


def   _snake_case    (    _snake_case					:      RealFunc			, _snake_case					:      RealFunc			, _snake_case					:      int			, ):
      lowerCAmelCase       :						Dict							= float(_snake_case      )
      while True:
            try:
                  lowerCAmelCase       :						Optional[Any]							= prev_guess - function(_snake_case      ) / derivative(_snake_case      )
            except ZeroDivisionError:
                  raise ZeroDivisionError('''Could not find root'''      ) from None
            if abs(prev_guess - next_guess      ) < 10**-5:
                  return next_guess
            lowerCAmelCase       :						Optional[int]							= next_guess


def   _snake_case    (    _snake_case					:      float      ):
      return (x**3) - (2 * x) - 5


def   _snake_case    (    _snake_case					:      float      ):
      return 3 * (x**2) - 2


if __name__ == "__main__":
 print(newton(f, fa, 3))


