"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

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


__A			   = logging.get_logger(__name__)

__A			   = {
    "facebook/data2vec-text-base": "https://huggingface.co/data2vec/resolve/main/config.json",
}


class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

    _UpperCAmelCase	:Union[str, Any]						    = "data2vec-text"






    def __init__(   self    ,			_UpperCAmelCase=30522    ,			_UpperCAmelCase=768    ,			_UpperCAmelCase=12    ,			_UpperCAmelCase=12    ,			_UpperCAmelCase=3072    ,			_UpperCAmelCase="gelu"    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=0.1    ,			_UpperCAmelCase=512    ,			_UpperCAmelCase=2    ,			_UpperCAmelCase=0.02    ,			_UpperCAmelCase=1e-1_2    ,			_UpperCAmelCase=1    ,			_UpperCAmelCase=0    ,			_UpperCAmelCase=2    ,			_UpperCAmelCase="absolute"    ,			_UpperCAmelCase=True    ,			_UpperCAmelCase=None    ,			**_UpperCAmelCase    ,			):
       super().__init__(pad_token_id=_UpperCAmelCase    ,			bos_token_id=_UpperCAmelCase    ,			eos_token_id=_UpperCAmelCase    ,			**_UpperCAmelCase							)

       lowercase__:   List[str]					=      vocab_size
       lowercase__:   Dict					=      hidden_size
       lowercase__:   Dict					=      num_hidden_layers
       lowercase__:   Union[str, Any]					=      num_attention_heads
       lowercase__:   List[Any]					=      hidden_act
       lowercase__:   int					=      intermediate_size
       lowercase__:   Union[str, Any]					=      hidden_dropout_prob
       lowercase__:   int					=      attention_probs_dropout_prob
       lowercase__:   str					=      max_position_embeddings
       lowercase__:   Dict					=      type_vocab_size
       lowercase__:   str					=      initializer_range
       lowercase__:   Optional[Any]					=      layer_norm_eps
       lowercase__:   str					=      position_embedding_type
       lowercase__:   Tuple					=      use_cache
       lowercase__:   str					=      classifier_dropout



class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

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

"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A			   = {
    "configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __A			   = [
           "LILT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "LiltForQuestionAnswering",
           "LiltForSequenceClassification",
           "LiltForTokenClassification",
           "LiltModel",
           "LiltPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_lilt import (
                  LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  LiltForQuestionAnswering,
                  LiltForSequenceClassification,
                  LiltForTokenClassification,
                  LiltModel,
                  LiltPreTrainedModel,
              )

else:
       import sys

       __A			   = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
