




'''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					       ='\\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
A					       ='\\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
A					       =''

# TODO: Add the licence for the dataset here if you can find it
A					       =''

# 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					       ={
    '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					):
       __a							:	List[Any]  							=   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')
       __a							:	Optional[int]  							=   [
           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"""					),
       ]

       __a							:	Tuple  							=   """first_domain"""  # It's not mandatory to have a default configuration. Just use one if it make sense.
       def        A (      self		:      List[str]							):



           '''simple docstring'''

           if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
               UpperCAmelCase     			=						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"
               UpperCAmelCase     			=						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=lowercase  ,							homepage=_HOMEPAGE  ,							license=_LICENSE  ,							citation=_CITATION  ,							)
       def        A (      self		:      Any  ,							lowercase		:      Optional[int]							):



           '''simple docstring'''

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







       def        A (      self		:      str  ,							lowercase		:      Optional[Any]  ,							lowercase		:      Union[str, Any]							):



           '''simple docstring'''

           with open(lowercase  ,							encoding='''utf-8'''							) as f:
               for key, row in enumerate(lowercase							):
                   UpperCAmelCase     			=						json.loads(lowercase							)
                   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 ...configuration_utils import PretrainedConfig
from ...utils import logging


A					       =logging.get_logger(__name__)

A					       ={
    'facebook/regnet-y-040': 'https://huggingface.co/facebook/regnet-y-040/blob/main/config.json',
}


class      _a    (      __a					):
       __a							:	Optional[int]  							=   """regnet"""
       __a							:	Optional[Any]  							=   ["""x""", """y"""]
       def __init__(      self		:      int  ,							lowercase		:      List[Any]=3  ,							lowercase		:      Union[str, Any]=32  ,							lowercase		:      Tuple=[128, 192, 512, 1_088]  ,							lowercase		:      List[Any]=[2, 6, 12, 2]  ,							lowercase		:      Optional[Any]=64  ,							lowercase		:      Optional[int]="y"  ,							lowercase		:      int="relu"  ,							**lowercase		:      int  ,							):



           '''simple docstring'''

           super().__init__(**lowercase							)
           if layer_type not in self.layer_types:
               raise ValueError(f"layer_type={layer_type} is not one of {','.join(self.layer_types							)}"							)
           UpperCAmelCase     			=						num_channels
           UpperCAmelCase     			=						embedding_size
           UpperCAmelCase     			=						hidden_sizes
           UpperCAmelCase     			=						depths
           UpperCAmelCase     			=						groups_width
           UpperCAmelCase     			=						layer_type
           UpperCAmelCase     			=						hidden_act
           # always downsample in the first stage
           UpperCAmelCase     			=						True




