
"""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 		_snake_case			(      lowercase__						:    List[Any] ,	**lowercase__						:    Any						)    ->							List[Any]:


			'''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 ,	**lowercase__ ,	)




class      _SCREAMING_SNAKE_CASE   (     A__				):






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






			def __init__(   self			,  __A			,  __A			,  __A			,  __A			,  __A			,  __A			,  __A			,  __A			,  __A			,  **__A			,  )     ->	Union[str, Any]:
						lowerCAmelCase_       :List[Any]     	=    dataset
						lowerCAmelCase_       :Any     	=    name
						lowerCAmelCase_       :Optional[int]     	=    cache_dir
						lowerCAmelCase_       :List[Any]     	=    beam_pipeline_options
						lowerCAmelCase_       :Any     	=    data_dir
						lowerCAmelCase_       :Any     	=    all_configs
						lowerCAmelCase_       :Dict     	=    save_infos
						lowerCAmelCase_       :int     	=    ignore_verifications
						lowerCAmelCase_       :Any     	=    force_redownload
						lowerCAmelCase_       :Any     	=    config_kwargs






			def 					__lowerCAmelCase					(   self			)     ->	Optional[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			)
						lowerCAmelCase_	,			lowerCAmelCase_       :Union[str, Any]     	=    self._dataset, self._name
						lowerCAmelCase_       :Tuple     	=    dataset_module_factory(__A			)
						lowerCAmelCase_       :Optional[int]     	=    import_main_class(dataset_module.module_path			)
						lowerCAmelCase_       :List[DatasetBuilder]     	=    []
						if self._beam_pipeline_options:
									lowerCAmelCase_       :Optional[int]     	=    beam.options.pipeline_options.PipelineOptions(
									    flags=[f"""--{opt.strip()}""" for opt in self._beam_pipeline_options.split(""","""			) if opt]			)
						else:
									lowerCAmelCase_       :Dict     	=    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=__A			,  cache_dir=self._cache_dir			,  base_path=dataset_module.builder_kwargs.get("""base_path"""			)			,  )			)
						else:
									builders.append(
									    builder_cls(
									        config_name=__A			,  data_dir=self._data_dir			,  beam_options=__A			,  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=__A			,  )
									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_       :str     	=    Path(__A			).name + """.py"""

									lowerCAmelCase_       :Union[str, Any]     	=    os.path.join(__A			,  __A			)
									if os.path.isfile(__A			):
												lowerCAmelCase_       :int     	=    os.path.dirname(__A			)
									elif os.path.isfile(__A			):
												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_       :Any     	=    os.path.join(__A			,  config.DATASETDICT_INFOS_FILENAME			)
									copyfile(__A			,  __A			)
									print(f"""Dataset Infos file saved at {user_dataset_infos_path}"""			)








"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCAmelCase 					=    {
    'configuration_marian': ['MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MarianConfig', 'MarianOnnxConfig'],
}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__UpperCAmelCase 					=    ['MarianTokenizer']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__UpperCAmelCase 					=    [
				    'MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'MarianForCausalLM',
				    'MarianModel',
				    'MarianMTModel',
				    'MarianPreTrainedModel',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__UpperCAmelCase 					=    ['TFMarianModel', 'TFMarianMTModel', 'TFMarianPreTrainedModel']

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__UpperCAmelCase 					=    ['FlaxMarianModel', 'FlaxMarianMTModel', 'FlaxMarianPreTrainedModel']

if TYPE_CHECKING:
				from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_marian import MarianTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_marian import (
								    MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MarianForCausalLM,
								    MarianModel,
								    MarianMTModel,
								    MarianPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
				import sys

				__UpperCAmelCase 					=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






