



from argparse import ArgumentParser

from . import BaseTransformersCLICommand






def  UpperCAmelCase__    (    lowercase__   ) ->      List[str]:
						return DownloadCommand(args.model						,       args.cache_dir						,       args.force						,       args.trust_remote_code   )







class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			@staticmethod
			def 		snake_case__			(				lowercase	:       ArgumentParser   )						->					str:
									"""simple docstring"""







									__lowercase					=				parser.add_parser("""download"""   )
									download_parser.add_argument(
									    """--cache-dir"""			,     type=lowercase			,     default=lowercase			,     help="""Path to location to store the models"""   )
									download_parser.add_argument(
									    """--force"""			,     action="""store_true"""			,     help="""Force the model to be download even if already in cache-dir"""   )
									download_parser.add_argument(
									    """--trust-remote-code"""			,     action="""store_true"""			,     help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""			,     )
									download_parser.add_argument("""model"""			,     type=lowercase			,     help="""Name of the model to download"""   )
									download_parser.set_defaults(func=lowercase   )





			def __init__(				self	:       int			,     lowercase	:       str			,     lowercase	:       str			,     lowercase	:       bool			,     lowercase	:       bool   )						->					Any:
									"""simple docstring"""







									__lowercase					=				model
									__lowercase					=				cache
									__lowercase					=				force
									__lowercase					=				trust_remote_code







			def 		snake_case__			(				self	:       Optional[Any]   )						->					List[str]:
									"""simple docstring"""







									from ..models.auto import AutoModel, AutoTokenizer

									AutoModel.from_pretrained(
									    self._model			,     cache_dir=self._cache			,     force_download=self._force			,     trust_remote_code=self._trust_remote_code   )
									AutoTokenizer.from_pretrained(
									    self._model			,     cache_dir=self._cache			,     force_download=self._force			,     trust_remote_code=self._trust_remote_code   )










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__ =						{
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "LukeForEntityClassification",
			    "LukeForEntityPairClassification",
			    "LukeForEntitySpanClassification",
			    "LukeForMultipleChoice",
			    "LukeForQuestionAnswering",
			    "LukeForSequenceClassification",
			    "LukeForTokenClassification",
			    "LukeForMaskedLM",
			    "LukeModel",
			    "LukePreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
			from .tokenization_luke import LukeTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_luke import (
						    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    LukeForEntityClassification,
						    LukeForEntityPairClassification,
						    LukeForEntitySpanClassification,
						    LukeForMaskedLM,
						    LukeForMultipleChoice,
						    LukeForQuestionAnswering,
						    LukeForSequenceClassification,
						    LukeForTokenClassification,
						    LukeModel,
						    LukePreTrainedModel,
						)

else:
			import sys

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





