"""simple docstring"""






import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile
from typing import List

from datasets import config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.info_utils import VerificationMode



def     a_		(   lowerCamelCase   ,     **lowerCamelCase			):
				return RunBeamCommand(
				    args.dataset   ,     args.name   ,     args.cache_dir   ,     args.beam_pipeline_options   ,     args.data_dir   ,     args.all_configs   ,     args.save_info or args.save_infos   ,     args.ignore_verifications   ,     args.force_redownload   ,     **lowerCamelCase   ,     )







class 							snake_case			(					__UpperCAmelCase							):




					"""simple docstring"""

					@staticmethod
					def 						__lowerCAmelCase		(							lowerCamelCase__  :      ArgumentParser     ):
									UpperCAmelCase__			 =				parser.add_parser('run_beam'       ,help='Run a Beam dataset processing pipeline'     )
									run_beam_parser.add_argument('dataset'       ,type=lowerCamelCase__       ,help='Name of the dataset to download'     )
									run_beam_parser.add_argument('--name'       ,type=lowerCamelCase__       ,default=lowerCamelCase__       ,help='Dataset config name'     )
									run_beam_parser.add_argument(
									    '--cache_dir'       ,type=lowerCamelCase__       ,default=lowerCamelCase__       ,help='Cache directory where the datasets are stored'       ,)
									run_beam_parser.add_argument(
									    '--beam_pipeline_options'       ,type=lowerCamelCase__       ,default=''       ,help='Beam pipeline options, separated by commas. Example:: `--beam_pipeline_options=job_name=my-job,project=my-project`'       ,)
									run_beam_parser.add_argument(
									    '--data_dir'       ,type=lowerCamelCase__       ,default=lowerCamelCase__       ,help='Can be used to specify a manual directory to get the files from'       ,)
									run_beam_parser.add_argument('--all_configs'       ,action='store_true'       ,help='Test all dataset configurations'     )
									run_beam_parser.add_argument('--save_info'       ,action='store_true'       ,help='Save the dataset infos file'     )
									run_beam_parser.add_argument(
									    '--ignore_verifications'       ,action='store_true'       ,help='Run the test without checksums and splits checks'     )
									run_beam_parser.add_argument('--force_redownload'       ,action='store_true'       ,help='Force dataset redownload'     )
									# aliases
									run_beam_parser.add_argument('--save_infos'       ,action='store_true'       ,help='alias for save_info'     )
									run_beam_parser.set_defaults(func=lowerCamelCase__     )







					def __init__(							self  :      Optional[int]       ,lowerCamelCase__  :      str       ,lowerCamelCase__  :      str       ,lowerCamelCase__  :      str       ,lowerCamelCase__  :      str       ,lowerCamelCase__  :      str       ,lowerCamelCase__  :      bool       ,lowerCamelCase__  :      bool       ,lowerCamelCase__  :      bool       ,lowerCamelCase__  :      bool       ,**lowerCamelCase__  :      Dict       ,):
									UpperCAmelCase__			 =				dataset
									UpperCAmelCase__			 =				name
									UpperCAmelCase__			 =				cache_dir
									UpperCAmelCase__			 =				beam_pipeline_options
									UpperCAmelCase__			 =				data_dir
									UpperCAmelCase__			 =				all_configs
									UpperCAmelCase__			 =				save_infos
									UpperCAmelCase__			 =				ignore_verifications
									UpperCAmelCase__			 =				force_redownload
									UpperCAmelCase__			 =				config_kwargs







					def 						__lowerCAmelCase		(							self  :      Any     ):
									import apache_beam as beam

									if self._name is not None and self._all_configs:
													print('Both parameters `name` and `all_configs` can\'t be used at once.'     )
													exit(1     )
									UpperCAmelCase__ ,      UpperCAmelCase__			 =				self._dataset, self._name
									UpperCAmelCase__			 =				dataset_module_factory(lowerCamelCase__     )
									UpperCAmelCase__			 =				import_main_class(dataset_module.module_path     )
									UpperCAmelCase__			 =				[]
									if self._beam_pipeline_options:
													UpperCAmelCase__			 =				beam.options.pipeline_options.PipelineOptions(
													    flags=[f'''--{opt.strip()}''' for opt in self._beam_pipeline_options.split(','     ) if opt]     )
									else:
													UpperCAmelCase__			 =				None
									if self._all_configs and len(builder_cls.BUILDER_CONFIGS     ) > 0:
													for builder_config in builder_cls.BUILDER_CONFIGS:
																	builders.append(
																	    builder_cls(
																	        config_name=builder_config.name       ,data_dir=self._data_dir       ,hash=dataset_module.hash       ,beam_options=lowerCamelCase__       ,cache_dir=self._cache_dir       ,base_path=dataset_module.builder_kwargs.get('base_path'     )       ,)     )
									else:
													builders.append(
													    builder_cls(
													        config_name=lowerCamelCase__       ,data_dir=self._data_dir       ,beam_options=lowerCamelCase__       ,cache_dir=self._cache_dir       ,base_path=dataset_module.builder_kwargs.get('base_path'     )       ,**self._config_kwargs       ,)     )

									for builder in builders:
													builder.download_and_prepare(
													    download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
													    if not self._force_redownload
													    else DownloadMode.FORCE_REDOWNLOAD       ,download_config=DownloadConfig(cache_dir=config.DOWNLOADED_DATASETS_PATH     )       ,verification_mode=VerificationMode.NO_CHECKS
													    if self._ignore_verifications
													    else VerificationMode.ALL_CHECKS       ,try_from_hf_gcs=lowerCamelCase__       ,)
													if self._save_infos:
																	builder._save_infos()

									print('Apache beam run successful.'     )

									# If save_infos=True, the dataset infos file is created next to the loaded module file.
									# Let's move it to the original directory of the dataset script, to allow the user to
									# upload them on S3 at the same time afterwards.
									if self._save_infos:
													UpperCAmelCase__			 =				os.path.join(builder_cls.get_imported_module_dir()       ,config.DATASETDICT_INFOS_FILENAME     )

													UpperCAmelCase__			 =				Path(lowerCamelCase__     ).name + '.py'

													UpperCAmelCase__			 =				os.path.join(lowerCamelCase__       ,lowerCamelCase__     )
													if os.path.isfile(lowerCamelCase__     ):
																	UpperCAmelCase__			 =				os.path.dirname(lowerCamelCase__     )
													elif os.path.isfile(lowerCamelCase__     ):
																	UpperCAmelCase__			 =				path
													else:  # in case of a remote dataset
																	print(f'''Dataset Infos file saved at {dataset_infos_path}'''     )
																	exit(1     )

													# Move datasetinfo back to the user
													UpperCAmelCase__			 =				os.path.join(lowerCamelCase__       ,config.DATASETDICT_INFOS_FILENAME     )
													copyfile(lowerCamelCase__       ,lowerCamelCase__     )
													print(f'''Dataset Infos file saved at {user_dataset_infos_path}'''     )




"""simple docstring"""






from sklearn.neural_network import MLPClassifier

lowerCAmelCase__    :    Any			=      [[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
lowerCAmelCase__    :    Optional[int]			=      [0, 1, 0, 0]


lowerCAmelCase__    :    Dict			=      MLPClassifier(
    solver='lbfgs', alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


lowerCAmelCase__    :    Optional[int]			=      [[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
lowerCAmelCase__    :    Union[str, Any]			=      clf.predict(test)



def     a_		(   lowerCamelCase			):
				return list(lowerCamelCase			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()



