






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase : Any						   =       logging.get_logger(__name__)

lowerCamelCase : Any						   =       {
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}

class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					_A						:			Union[str, Any]									=      '''roberta-prelayernorm'''



					def __init__(  self				:	List[str]		,     __a				:	List[str]=50265		,     __a				:	str=768		,     __a				:	Optional[int]=12		,     __a				:	List[Any]=12		,     __a				:	Tuple=3072		,     __a				:	int="gelu"		,     __a				:	List[str]=0.1		,     __a				:	List[str]=0.1		,     __a				:	Dict=512		,     __a				:	Union[str, Any]=2		,     __a				:	List[Any]=0.02		,     __a				:	Optional[int]=1E-12		,     __a				:	Union[str, Any]=1		,     __a				:	List[str]=0		,     __a				:	List[Any]=2		,     __a				:	int="absolute"		,     __a				:	Tuple=True		,     __a				:	List[Any]=None		,     **__a				:	Optional[int]		,     )			->  Union[str, Any]:


												"""simple docstring"""

												super().__init__(pad_token_id=__a		,     bos_token_id=__a		,     eos_token_id=__a		,     **__a							)

												__lowercase      :							str				=     vocab_size
												__lowercase      :							Optional[int]				=     hidden_size
												__lowercase      :							Optional[int]				=     num_hidden_layers
												__lowercase      :							Optional[int]				=     num_attention_heads
												__lowercase      :							List[str]				=     hidden_act
												__lowercase      :							Dict				=     intermediate_size
												__lowercase      :							Optional[int]				=     hidden_dropout_prob
												__lowercase      :							Optional[int]				=     attention_probs_dropout_prob
												__lowercase      :							Dict				=     max_position_embeddings
												__lowercase      :							Any				=     type_vocab_size
												__lowercase      :							List[Any]				=     initializer_range
												__lowercase      :							List[Any]				=     layer_norm_eps
												__lowercase      :							List[str]				=     position_embedding_type
												__lowercase      :							int				=     use_cache
												__lowercase      :							List[Any]				=     classifier_dropout







class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					@property
					def       lowerCAmelCase				(  self				:	Union[str, Any]							)			->  Mapping[str, Mapping[int, str]]:


												"""simple docstring"""

												if self.task == "multiple-choice":
																			__lowercase      :							Dict				=     {0: """batch""", 1: """choice""", 2: """sequence"""}
												else:
																			__lowercase      :							List[Any]				=     {0: """batch""", 1: """sequence"""}
												return OrderedDict(
												    [
												        ("""input_ids""", dynamic_axis),
												        ("""attention_mask""", dynamic_axis),
												    ]							)







from argparse import ArgumentParser

from . import BaseTransformersCLICommand
def       snake_case_		(     lowerCAmelCase_       :						Dict      ):
							return DownloadCommand(args.model       ,       args.cache_dir       ,       args.force       ,       args.trust_remote_code      )



class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					@staticmethod
					def       lowerCAmelCase				(  __a				:	ArgumentParser							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     parser.add_parser("""download"""							)
												download_parser.add_argument(
												    """--cache-dir"""		,     type=__a		,     default=__a		,     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=__a		,     help="""Name of the model to download"""							)
												download_parser.set_defaults(func=__a							)



					def __init__(  self				:	Dict		,     __a				:	str		,     __a				:	str		,     __a				:	bool		,     __a				:	bool							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							Dict				=     model
												__lowercase      :							List[Any]				=     cache
												__lowercase      :							Any				=     force
												__lowercase      :							Optional[int]				=     trust_remote_code



					def       lowerCAmelCase				(  self				:	str							)			->  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							)