
from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE							:str							 =				logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							:Tuple							 =				{
    'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/config.json',
    'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/config.json',
    'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/config.json',
    'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/config.json',
    'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json',
    'roberta-large-openai-detector': 'https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json',
}





class 							UpperCAmelCase      (  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	snake_case_					    =     "roberta"






	def __init__(       self					: Optional[int]							,A					: Optional[int]=5_02_65							,A					: Union[str, Any]=7_68							,A					: Tuple=12							,A					: Any=12							,A					: List[Any]=30_72							,A					: str="gelu"							,A					: Dict=0.1							,A					: Union[str, Any]=0.1							,A					: Dict=5_12							,A					: Union[str, Any]=2							,A					: Tuple=0.02							,A					: Dict=1E-12							,A					: Optional[Any]=1							,A					: int=0							,A					: Union[str, Any]=2							,A					: str="absolute"							,A					: Optional[int]=True							,A					: Dict=None							,**A					: Optional[Any]							,):
					super().__init__(pad_token_id=A							,bos_token_id=A							,eos_token_id=A							,**A )

					__A   			= vocab_size
					__A   			= hidden_size
					__A   			= num_hidden_layers
					__A   			= num_attention_heads
					__A   			= hidden_act
					__A   			= intermediate_size
					__A   			= hidden_dropout_prob
					__A   			= attention_probs_dropout_prob
					__A   			= max_position_embeddings
					__A   			= type_vocab_size
					__A   			= initializer_range
					__A   			= layer_norm_eps
					__A   			= position_embedding_type
					__A   			= use_cache
					__A   			= classifier_dropout





class 							UpperCAmelCase      (  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





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




"""simple docstring"""




import warnings

from ..trainer import Trainer
from ..utils import logging


lowercase_			     =  logging.get_logger(__name__)
class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		def __init__(  self							, _a=None							, **_a      ):
				warnings.warn(
				    '''`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` '''
				    '''instead.'''							, _a							, )
				super().__init__(args=_a							, **_a      )






