'''simple docstring'''




from typing import TYPE_CHECKING

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


_lowercase		:					Dict													=		{
    "configuration_splinter": ["SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SplinterConfig"],
    "tokenization_splinter": ["SplinterTokenizer"],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase		:					Optional[int]													=		["SplinterTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase		:					Any													=		[
						    "SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SplinterForQuestionAnswering",
						    "SplinterForPreTraining",
						    "SplinterLayer",
						    "SplinterModel",
						    "SplinterPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
						from .tokenization_splinter import SplinterTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_splinter_fast import SplinterTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_splinter import (
												    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SplinterForPreTraining,
												    SplinterForQuestionAnswering,
												    SplinterLayer,
												    SplinterModel,
												    SplinterPreTrainedModel,
												)


else:
						import sys

						_lowercase		:					Any													=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






'''simple docstring'''




from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments




def 				lowerCamelCase      ( )     -> List[Any]:
							lowercase_   :     Tuple									=			HfArgumentParser(UpperCAmelCase__					)
							try:
														lowercase_   :     List[Any]									=			parser.parse_args_into_dataclasses()[0]
							except ValueError as e:
														lowercase_   :     int									=			"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
														lowercase_   :     Any									=			""" """.join(str(UpperCAmelCase__					).split(""" """					)[:-1]					)
														lowercase_   :     Optional[Any]									=			""""""
														lowercase_   :     List[str]									=			eval(str(UpperCAmelCase__					).split(""" """					)[-1]					)
														lowercase_   :     Dict									=			[]
														for arg in depreciated_args:
																					# arg[2:] removes '--'
																					if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
																												# arg[5:] removes '--no_'
																												full_error_msg += arg_error_msg.format(arg[5:]					)
																					else:
																												wrong_args.append(UpperCAmelCase__					)
														if len(UpperCAmelCase__					) > 0:
																					lowercase_   :     Dict									=			full_error_msg + begin_error_msg + str(UpperCAmelCase__					)
														raise ValueError(UpperCAmelCase__					)

							lowercase_   :     Optional[int]									=			PyTorchBenchmark(args=UpperCAmelCase__					)
							benchmark.run()


if __name__ == "__main__":
						main()





