from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__     :	str				=			logging.get_logger(__name__)

UpperCamelCase__     :	List[str]				=			{
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}


class 				_lowercase	(      lowerCAmelCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Union[str, Any]      							=   '''lilt'''




      def __init__(				self					,lowerCamelCase_=30522					,lowerCamelCase_=768					,lowerCamelCase_=12					,lowerCamelCase_=12					,lowerCamelCase_=3072					,lowerCamelCase_="gelu"					,lowerCamelCase_=0.1					,lowerCamelCase_=0.1					,lowerCamelCase_=512					,lowerCamelCase_=2					,lowerCamelCase_=0.02					,lowerCamelCase_=1e-12					,lowerCamelCase_=0					,lowerCamelCase_="absolute"					,lowerCamelCase_=None					,lowerCamelCase_=4					,lowerCamelCase_=1024					,**lowerCamelCase_					,)			->			Union[str, Any]:



         '''simple docstring'''



         super().__init__(pad_token_id=lowerCamelCase_					,**lowerCamelCase_							)

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





'''simple docstring'''

from typing import TYPE_CHECKING

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


UpperCamelCase__     :	List[Any]				=			{'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__     :	int				=			['YolosFeatureExtractor']
  UpperCamelCase__     :	int				=			['YolosImageProcessor']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__     :	int				=			[
      'YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST',
      'YolosForObjectDetection',
      'YolosModel',
      'YolosPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig, YolosOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_yolos import YolosFeatureExtractor
    from .image_processing_yolos import YolosImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_yolos import (
        YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST,
        YolosForObjectDetection,
        YolosModel,
        YolosPreTrainedModel,
    )


else:
  import sys

  UpperCamelCase__     :	int				=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




