



'''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 	__lowerCAmelCase       (				lowerCamelCase :    Any					,		**lowerCamelCase :    str       ):






	'''simple docstring'''




	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        UpperCAmelCase__						(		UpperCamelCase__			):



					@staticmethod
					def 							UpperCAmelCase_			(     UpperCamelCase  )  ->      Any:
						__lowerCAmelCase       				=	parser.add_parser("run_beam"      ,					help="Run a Beam dataset processing pipeline"  )
						run_beam_parser.add_argument("dataset"      ,					type=UpperCamelCase      ,					help="Name of the dataset to download"  )
						run_beam_parser.add_argument("--name"      ,					type=UpperCamelCase      ,					default=UpperCamelCase      ,					help="Dataset config name"  )
						run_beam_parser.add_argument(
						    "--cache_dir"      ,					type=UpperCamelCase      ,					default=UpperCamelCase      ,					help="Cache directory where the datasets are stored"      ,					)
						run_beam_parser.add_argument(
						    "--beam_pipeline_options"      ,					type=UpperCamelCase      ,					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=UpperCamelCase      ,					default=UpperCamelCase      ,					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=UpperCamelCase  )



					def __init__(     self      ,					UpperCamelCase      ,					UpperCamelCase      ,					UpperCamelCase      ,					UpperCamelCase      ,					UpperCamelCase      ,					UpperCamelCase      ,					UpperCamelCase      ,					UpperCamelCase      ,					UpperCamelCase      ,					**UpperCamelCase      ,					)  ->      Union[str, Any]:
						__lowerCAmelCase       				=	dataset
						__lowerCAmelCase       				=	name
						__lowerCAmelCase       				=	cache_dir
						__lowerCAmelCase       				=	beam_pipeline_options
						__lowerCAmelCase       				=	data_dir
						__lowerCAmelCase       				=	all_configs
						__lowerCAmelCase       				=	save_infos
						__lowerCAmelCase       				=	ignore_verifications
						__lowerCAmelCase       				=	force_redownload
						__lowerCAmelCase       				=	config_kwargs



					def 							UpperCAmelCase_			(     self  )  ->      int:
						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  )
						__lowerCAmelCase				,							__lowerCAmelCase       				=	self._dataset, self._name
						__lowerCAmelCase       				=	dataset_module_factory(UpperCamelCase  )
						__lowerCAmelCase       				=	import_main_class(dataset_module.module_path  )
						__lowerCAmelCase       				=	[]
						if self._beam_pipeline_options:
							__lowerCAmelCase       				=	beam.options.pipeline_options.PipelineOptions(
							    flags=[F'''--{opt.strip()}''' for opt in self._beam_pipeline_options.split(","  ) if opt]  )
						else:
							__lowerCAmelCase       				=	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=UpperCamelCase      ,					cache_dir=self._cache_dir      ,					base_path=dataset_module.builder_kwargs.get("base_path"  )      ,					)  )
						else:
							builders.append(
							    builder_cls(
							        config_name=UpperCamelCase      ,					data_dir=self._data_dir      ,					beam_options=UpperCamelCase      ,					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=UpperCamelCase      ,					)
							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:
							__lowerCAmelCase       				=	os.path.join(builder_cls.get_imported_module_dir()      ,					config.DATASETDICT_INFOS_FILENAME  )

							__lowerCAmelCase       				=	Path(UpperCamelCase  ).name + ".py"

							__lowerCAmelCase       				=	os.path.join(UpperCamelCase      ,					UpperCamelCase  )
							if os.path.isfile(UpperCamelCase  ):
								__lowerCAmelCase       				=	os.path.dirname(UpperCamelCase  )
							elif os.path.isfile(UpperCamelCase  ):
								__lowerCAmelCase       				=	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
							__lowerCAmelCase       				=	os.path.join(UpperCamelCase      ,					config.DATASETDICT_INFOS_FILENAME  )
							copyfile(UpperCamelCase      ,					UpperCamelCase  )
							print(F'''Dataset Infos file saved at {user_dataset_infos_path}'''  )




'''simple docstring'''



lowerCAmelCase						:		Tuple						      = '''
# Diffusers installation
! pip install diffusers transformers datasets accelerate
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/diffusers.git
'''

lowerCAmelCase						:		Tuple						      = [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]