
"""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_     (	snake_case_	:    Union[str, Any]							,					**snake_case_	:    List[str]    )     ->List[Any]:
			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							,					**snake_case_							,					)

class 					A_			(  _a     ):





							@staticmethod
							def    UpperCAmelCase__							(						lowerCamelCase_						:Tuple ):





										"""simple docstring"""

										lowerCamelCase__			:  Any  =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						:str  ,							lowerCamelCase_						:Dict  ,							lowerCamelCase_						:Dict  ,							lowerCamelCase_						:Dict  ,							lowerCamelCase_						:int  ,							lowerCamelCase_						:Any  ,							lowerCamelCase_						:Any  ,							lowerCamelCase_						:Optional[int]  ,							lowerCamelCase_						:Optional[Any]  ,							lowerCamelCase_						:Dict  ,							**lowerCamelCase_						:List[str]  ,							):





										"""simple docstring"""

										lowerCamelCase__			:  List[str]  =dataset
										lowerCamelCase__			:  List[str]  =name
										lowerCamelCase__			:  str  =cache_dir
										lowerCamelCase__			:  Optional[Any]  =beam_pipeline_options
										lowerCamelCase__			:  Union[str, Any]  =data_dir
										lowerCamelCase__			:  int  =all_configs
										lowerCamelCase__			:  List[str]  =save_infos
										lowerCamelCase__			:  Optional[int]  =ignore_verifications
										lowerCamelCase__			:  Union[str, Any]  =force_redownload
										lowerCamelCase__			:  Any  =config_kwargs





							def    UpperCAmelCase__							(						self						:Any ):





										"""simple docstring"""

										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__			:  List[str]  =self._dataset, self._name
										lowerCamelCase__			:  List[Any]  =dataset_module_factory(lowerCamelCase__ )
										lowerCamelCase__			:  Union[str, Any]  =import_main_class(dataset_module.module_path )
										lowerCamelCase__			:  List[DatasetBuilder]  =[]
										if self._beam_pipeline_options:
													lowerCamelCase__			:  Union[str, Any]  =beam.options.pipeline_options.PipelineOptions(
													    flags=[f"""--{opt.strip()}""" for opt in self._beam_pipeline_options.split(',' ) if opt] )
										else:
													lowerCamelCase__			:  Optional[int]  =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:
													lowerCamelCase__			:  Any  =os.path.join(builder_cls.get_imported_module_dir()  ,							config.DATASETDICT_INFOS_FILENAME )

													lowerCamelCase__			:  Dict  =Path(lowerCamelCase__ ).name + ".py"

													lowerCamelCase__			:  Tuple  =os.path.join(lowerCamelCase__  ,							lowerCamelCase__ )
													if os.path.isfile(lowerCamelCase__ ):
																lowerCamelCase__			:  Optional[int]  =os.path.dirname(lowerCamelCase__ )
													elif os.path.isfile(lowerCamelCase__ ):
																lowerCamelCase__			:  Any  =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__			:  Optional[int]  =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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCAmelCase			=		{
    """configuration_donut_swin""": ["""DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DonutSwinConfig"""],
    """processing_donut""": ["""DonutProcessor"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase			=		[
							    """DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """DonutSwinModel""",
							    """DonutSwinPreTrainedModel""",
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase			=		["""DonutFeatureExtractor"""]
							lowerCAmelCase			=		["""DonutImageProcessor"""]


if TYPE_CHECKING:
							from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
							from .processing_donut import DonutProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_donut_swin import (
														    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DonutSwinModel,
														    DonutSwinPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_donut import DonutFeatureExtractor
														from .image_processing_donut import DonutImageProcessor

else:
							import sys

							lowerCAmelCase			=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)