




from collections import OrderedDict
from typing import Mapping

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


_lowerCamelCase     :		Optional[int]								=       logging.get_logger(__name__)

_lowerCamelCase     :		Union[str, 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     UpperCamelCase_   (			UpperCAmelCase__					):

    '''simple docstring'''






    UpperCAmelCase__							  =				'''xlm-roberta-xl'''


    def __init__(      self				:     str ,			UpperCAmelCase__				:     str=250_880 ,			UpperCAmelCase__				:     Union[str, Any]=2_560 ,			UpperCAmelCase__				:     str=36 ,			UpperCAmelCase__				:     str=32 ,			UpperCAmelCase__				:     List[str]=10_240 ,			UpperCAmelCase__				:     Optional[int]="gelu" ,			UpperCAmelCase__				:     Optional[int]=0.1 ,			UpperCAmelCase__				:     int=0.1 ,			UpperCAmelCase__				:     Dict=514 ,			UpperCAmelCase__				:     Any=1 ,			UpperCAmelCase__				:     Union[str, Any]=0.02 ,			UpperCAmelCase__				:     Union[str, Any]=1e-05 ,			UpperCAmelCase__				:     List[str]=1 ,			UpperCAmelCase__				:     Tuple=0 ,			UpperCAmelCase__				:     Any=2 ,			UpperCAmelCase__				:     List[Any]="absolute" ,			UpperCAmelCase__				:     Dict=True ,			UpperCAmelCase__				:     str=None ,			**UpperCAmelCase__				:     str ,			)						->int:





           '''simple docstring'''

           super().__init__(pad_token_id=UpperCAmelCase__ ,			bos_token_id=UpperCAmelCase__ ,			eos_token_id=UpperCAmelCase__ ,			**UpperCAmelCase__)
           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_   (			UpperCAmelCase__					):

    '''simple docstring'''






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





           '''simple docstring'''

           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),
               ])








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_lowerCamelCase     :		Union[str, Any]								=       {
    """configuration_swiftformer""": [
        """SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwiftFormerConfig""",
        """SwiftFormerOnnxConfig""",
    ]
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Union[str, Any]								=       [
      """SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """SwiftFormerForImageClassification""",
      """SwiftFormerModel""",
      """SwiftFormerPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_swiftformer import (
      SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      SwiftFormerConfig,
      SwiftFormerOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_swiftformer import (
        SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        SwiftFormerForImageClassification,
        SwiftFormerModel,
        SwiftFormerPreTrainedModel,
    )

else:
  import sys

  _lowerCamelCase     :		str								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


