


from collections import OrderedDict
from typing import Mapping

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


A				:       List[Any]      =  logging.get_logger(__name__)

A				:       str      =  {
    'facebook/xlm-roberta-xl': 'https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json',
    'facebook/xlm-roberta-xxl': 'https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}






class      UpperCamelCase(	UpperCAmelCase__ ):
					snake_case_		:					str    					=						'''xlm-roberta-xl'''


					def __init__(    self						:		List[str]  ,     SCREAMING_SNAKE_CASE						:		Optional[int]=2_5_0_8_8_0  ,     SCREAMING_SNAKE_CASE						:		str=2_5_6_0  ,     SCREAMING_SNAKE_CASE						:		Dict=3_6  ,     SCREAMING_SNAKE_CASE						:		Any=3_2  ,     SCREAMING_SNAKE_CASE						:		Dict=1_0_2_4_0  ,     SCREAMING_SNAKE_CASE						:		Tuple="gelu"  ,     SCREAMING_SNAKE_CASE						:		List[str]=0.1  ,     SCREAMING_SNAKE_CASE						:		Union[str, Any]=0.1  ,     SCREAMING_SNAKE_CASE						:		int=5_1_4  ,     SCREAMING_SNAKE_CASE						:		int=1  ,     SCREAMING_SNAKE_CASE						:		Dict=0.02  ,     SCREAMING_SNAKE_CASE						:		Any=1e-0_5  ,     SCREAMING_SNAKE_CASE						:		str=1  ,     SCREAMING_SNAKE_CASE						:		List[str]=0  ,     SCREAMING_SNAKE_CASE						:		int=2  ,     SCREAMING_SNAKE_CASE						:		List[str]="absolute"  ,     SCREAMING_SNAKE_CASE						:		Tuple=True  ,     SCREAMING_SNAKE_CASE						:		List[Any]=None  ,     **SCREAMING_SNAKE_CASE						:		Union[str, Any]  ,     )      ->						Dict:




											'''simple docstring'''

											super().__init__(pad_token_id=__lowerCAmelCase  ,     bos_token_id=__lowerCAmelCase  ,     eos_token_id=__lowerCAmelCase  ,     **__lowerCAmelCase    )
											__snake_case				=		vocab_size
											__snake_case				=		hidden_size
											__snake_case				=		num_hidden_layers
											__snake_case				=		num_attention_heads
											__snake_case				=		hidden_act
											__snake_case				=		intermediate_size
											__snake_case				=		hidden_dropout_prob
											__snake_case				=		attention_probs_dropout_prob
											__snake_case				=		max_position_embeddings
											__snake_case				=		type_vocab_size
											__snake_case				=		initializer_range
											__snake_case				=		layer_norm_eps
											__snake_case				=		position_embedding_type
											__snake_case				=		use_cache
											__snake_case				=		classifier_dropout






class      UpperCamelCase(	UpperCAmelCase__ ):


					@property
					def 				SCREAMING_SNAKE_CASE_	(    self						:		Tuple    )      ->						List[str]:




											'''simple docstring'''

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











'''simple docstring'''


from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *

