
'''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__      :       int 		=						"\\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__      :       List[Any] 		=						"\\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__      :       Any 		=						""

# TODO: Add the licence for the dataset here if you can find it
UpperCAmelCase__      :       Union[str, 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)
UpperCAmelCase__      :       List[Any] 		=						{
    "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			):
	snake_case__					:Tuple         =   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__					:List[Any]         =   [
	    datasets.BuilderConfig(name='first_domain'     ,					version=lowerCAmelCase__     ,					description='This part of my dataset covers a first domain'			),
	    datasets.BuilderConfig(name='second_domain'     ,					version=lowerCAmelCase__     ,					description='This part of my dataset covers a second domain'			),
	]

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





	def 							__SCREAMING_SNAKE_CASE     (    self	:				Optional[int]							):


				"""simple docstring"""

				if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
							lowerCAmelCase__									=							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__									=							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=_lowerCamelCase					,							homepage=_HOMEPAGE					,							license=_LICENSE					,							citation=_CITATION					,							)





	def 							__SCREAMING_SNAKE_CASE     (    self	:				Dict					,							__magic_name__	:				Union[str, Any]							):


				"""simple docstring"""

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







	def 							__SCREAMING_SNAKE_CASE     (    self	:				Union[str, Any]					,							__magic_name__	:				List[str]					,							__magic_name__	:				int							):


				"""simple docstring"""

				with open(_lowerCamelCase					,							encoding="utf-8"							) as f:
							for key, row in enumerate(_lowerCamelCase							):
										lowerCAmelCase__									=							json.loads(_lowerCamelCase							)
										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 torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig






class 							__lowercase				(					lowerCAmelCase__  ):







	'''simple docstring'''

	a			: Union[str, Any]      =				CustomConfig


	def __init__(self   ,_lowerCamelCase       )							->							Tuple:







				'''simple docstring'''





				super().__init__(_lowerCamelCase       )
				__lowercase   =							torch.nn.Linear(config.hidden_size   ,config.hidden_size       )


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							List[str]:







				'''simple docstring'''





				return self.linear(_lowerCamelCase       )


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							List[Any]:







				'''simple docstring'''





				pass






class 							__lowercase				(					lowerCAmelCase__  ):







	'''simple docstring'''

	a			: Dict      =				NoSuperInitConfig


	def __init__(self   ,_lowerCamelCase       )							->							str:







				'''simple docstring'''





				super().__init__(_lowerCamelCase       )
				__lowercase   =							torch.nn.Linear(config.attribute   ,config.attribute       )


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							List[str]:







				'''simple docstring'''





				return self.linear(_lowerCamelCase       )


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							Tuple:







				'''simple docstring'''





				pass





