





from collections import OrderedDict
from typing import Mapping

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


_SCREAMING_SNAKE_CASE      	=		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE      	=		{
    """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/config.json""",
    """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/config.json""",
    """xlm-roberta-large-finetuned-conll02-dutch""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll02-spanish""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll03-english""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll03-german""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"""
    ),
}
class SCREAMING_SNAKE_CASE_						(					snake_case_					):
						__magic_name__:			Any       =       "xlm-roberta"






						def __init__(      self      :      int		,   _A      :      int=30522		,   _A      :      List[Any]=768		,   _A      :      Optional[Any]=12		,   _A      :      List[str]=12		,   _A      :      int=3072		,   _A      :      int="gelu"		,   _A      :      Optional[int]=0.1		,   _A      :      Tuple=0.1		,   _A      :      List[Any]=512		,   _A      :      Tuple=2		,   _A      :      List[str]=0.0_2		,   _A      :      str=1E-12		,   _A      :      Optional[Any]=1		,   _A      :      List[str]=0		,   _A      :      Dict=2		,   _A      :      Dict="absolute"		,   _A      :      List[str]=True		,   _A      :      Union[str, Any]=None		,   **_A      :      List[str]		,   )							->    Optional[int]:







							"""simple docstring"""


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

							snake_case_		:			Dict											=	vocab_size
							snake_case_		:			Optional[int]											=	hidden_size
							snake_case_		:			str											=	num_hidden_layers
							snake_case_		:			Dict											=	num_attention_heads
							snake_case_		:			Dict											=	hidden_act
							snake_case_		:			Optional[Any]											=	intermediate_size
							snake_case_		:			Optional[int]											=	hidden_dropout_prob
							snake_case_		:			str											=	attention_probs_dropout_prob
							snake_case_		:			Any											=	max_position_embeddings
							snake_case_		:			Tuple											=	type_vocab_size
							snake_case_		:			int											=	initializer_range
							snake_case_		:			str											=	layer_norm_eps
							snake_case_		:			Optional[Any]											=	position_embedding_type
							snake_case_		:			str											=	use_cache
							snake_case_		:			List[str]											=	classifier_dropout
class SCREAMING_SNAKE_CASE_						(					snake_case_					):






						@property
						def UpperCAmelCase_				(      self      :      str	)							->    Mapping[str, Mapping[int, str]]:







							"""simple docstring"""


							if self.task == "multiple-choice":
								snake_case_		:			Optional[int]											=	{0: 'batch', 1: 'choice', 2: 'sequence'}
							else:
								snake_case_		:			Union[str, Any]											=	{0: 'batch', 1: 'sequence'}
							return OrderedDict(
							    [
							        ('input_ids', dynamic_axis),
							        ('attention_mask', dynamic_axis),
							    ]	)








from ....utils import logging


_SCREAMING_SNAKE_CASE      	=		logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE_						(					snake_case_					):






						def __init__(      self      :      str		,   _A      :      List[Any]		,   _A      :      List[Any]=None		,   _A      :      str=2048	)							->    Optional[int]:







							"""simple docstring"""


							snake_case_		:			Tuple											=	config.__dict__
							snake_case_		:			List[str]											=	modal_hidden_size
							if num_labels:
								snake_case_		:			int											=	num_labels

