




from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase__ :   List[str]					=							logging.get_logger(__name__)

lowerCamelCase__ :   Any					=							{
    '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        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







 lowercase_				    =    "xlm-roberta-xl"



 def __init__(							self  :		int				,				_lowerCAmelCase  :		Any=250_880				,				_lowerCAmelCase  :		int=2_560				,				_lowerCAmelCase  :		List[Any]=36				,				_lowerCAmelCase  :		Union[str, Any]=32				,				_lowerCAmelCase  :		Optional[int]=10_240				,				_lowerCAmelCase  :		List[str]="gelu"				,				_lowerCAmelCase  :		Union[str, Any]=0.1				,				_lowerCAmelCase  :		Tuple=0.1				,				_lowerCAmelCase  :		Any=514				,				_lowerCAmelCase  :		int=1				,				_lowerCAmelCase  :		Optional[Any]=0.02				,				_lowerCAmelCase  :		List[str]=1E-05				,				_lowerCAmelCase  :		List[Any]=1				,				_lowerCAmelCase  :		List[Any]=0				,				_lowerCAmelCase  :		int=2				,				_lowerCAmelCase  :		Union[str, Any]="absolute"				,				_lowerCAmelCase  :		Any=True				,				_lowerCAmelCase  :		int=None				,				**_lowerCAmelCase  :		int				,				):
       super().__init__(pad_token_id=_lowerCAmelCase				,				bos_token_id=_lowerCAmelCase				,				eos_token_id=_lowerCAmelCase				,				**_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_							=			vocab_size
       SCREAMING_SNAKE_CASE_							=			hidden_size
       SCREAMING_SNAKE_CASE_							=			num_hidden_layers
       SCREAMING_SNAKE_CASE_							=			num_attention_heads
       SCREAMING_SNAKE_CASE_							=			hidden_act
       SCREAMING_SNAKE_CASE_							=			intermediate_size
       SCREAMING_SNAKE_CASE_							=			hidden_dropout_prob
       SCREAMING_SNAKE_CASE_							=			attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE_							=			max_position_embeddings
       SCREAMING_SNAKE_CASE_							=			type_vocab_size
       SCREAMING_SNAKE_CASE_							=			initializer_range
       SCREAMING_SNAKE_CASE_							=			layer_norm_eps
       SCREAMING_SNAKE_CASE_							=			position_embedding_type
       SCREAMING_SNAKE_CASE_							=			use_cache
       SCREAMING_SNAKE_CASE_							=			classifier_dropout





class        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







 @property
 def       lowerCAmelCase_  (							self  :		str						):
       if self.task == "multiple-choice":
             SCREAMING_SNAKE_CASE_							=			{0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
             SCREAMING_SNAKE_CASE_							=			{0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ('input_ids', dynamic_axis),
               ('attention_mask', dynamic_axis),
           ]						)





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase__ :   str					=							{
    'configuration_mask2former': [
        'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Mask2FormerConfig',
    ],
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__ :   int					=							['Mask2FormerImageProcessor']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__ :   Dict					=							[
       'MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'Mask2FormerForUniversalSegmentation',
       'Mask2FormerModel',
       'Mask2FormerPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_maskaformer import MaskaFormerImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_maskaformer import (
          MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          MaskaFormerForUniversalSegmentation,
          MaskaFormerModel,
          MaskaFormerPreTrainedModel,
      )


else:
   import sys

   lowerCamelCase__ :   Tuple					=							_LazyModule(__name__, globals()['__file__'], _import_structure)