






"""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
a :				str      					=		"""\
@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
a :				int      					=		"""\
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
a :				Optional[Any]      					=		""""""

# TODO: Add the licence for the dataset here if you can find it
a :				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)
a :				Any      					=		{
    """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"""




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




						def 		UpperCAmelCase_       (   self			):
												'''simple docstring'''
												# 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
																		lowercase__				:      Any=       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__				:      Optional[int]=       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__			):
												'''simple docstring'''
												# 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
												lowercase__				:      List[str]=       _URLS[self.config.name]
												lowercase__				:      Optional[Any]=       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__			):
												'''simple docstring'''
												# 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(snake_case__       ,  encoding="utf-8"			) as f:
																		for key, row in enumerate(snake_case__			):
																								lowercase__				:      Optional[int]=       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 math
from decimal import Decimal, getcontext





def 						lowercase__(A = 4_000_000						)				->int:




						"""simple docstring"""



						try:
												lowercase__				:      int=       int(A						)
						except (TypeError, ValueError):
												raise TypeError("Parameter n must be int or castable to int."						)
						if n <= 0:
												raise ValueError("Parameter n must be greater than or equal to one."						)
						lowercase__				:      Dict=       100
						lowercase__				:      Optional[Any]=       (Decimal(5						) ** Decimal(0.5						) + 1) / Decimal(2						)

						lowercase__				:      str=       (math.floor(math.log(n * (phi + 2)					,		A						) - 1						) // 3) * 3 + 2
						lowercase__				:      Optional[Any]=       Decimal(round(phi ** Decimal(index + 1						)						)						) / (phi + 2)
						lowercase__				:      Tuple=       num // 2
						return int(A						)


if __name__ == "__main__":
			print(F"""{solution() = }""")






