code: from ...configuration_utils import PretrainedConfig
  from ...utils import is_detectrona_available, logging
  
  
  A_:      Union[str, Any]        =			logging.get_logger(__name__)
  
  A_:      int        =			{
      'layoutlmv2-base-uncased': 'https://huggingface.co/microsoft/layoutlmv2-base-uncased/resolve/main/config.json',
      'layoutlmv2-large-uncased': 'https://huggingface.co/microsoft/layoutlmv2-large-uncased/resolve/main/config.json',
      # See all LayoutLMv2 models at https://huggingface.co/models?filter=layoutlmv2
  }
  
  # soft dependency
  if is_detectrona_available():
  				import detectrona
  
  
  class _lowercase					(       _UpperCAmelCase						):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  							lowerCAmelCase__       =					'layoutlmv2'
  
  
  
  							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-12     ,   UpperCAmelCase=0     ,   UpperCAmelCase=1024     ,   UpperCAmelCase=128     ,   UpperCAmelCase=32     ,   UpperCAmelCase=True     ,   UpperCAmelCase=256     ,   UpperCAmelCase=64     ,   UpperCAmelCase=True     ,   UpperCAmelCase=[7, 7, 256]     ,   UpperCAmelCase=128     ,   UpperCAmelCase=128     ,   UpperCAmelCase=True     ,   UpperCAmelCase=True     ,   UpperCAmelCase=False     ,   UpperCAmelCase=None     ,   **UpperCAmelCase     ,   ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														super().__init__(
  														    vocab_size=UpperCAmelCase     ,   hidden_size=UpperCAmelCase     ,   num_hidden_layers=UpperCAmelCase     ,   num_attention_heads=UpperCAmelCase     ,   intermediate_size=UpperCAmelCase     ,   hidden_act=UpperCAmelCase     ,   hidden_dropout_prob=UpperCAmelCase     ,   attention_probs_dropout_prob=UpperCAmelCase     ,   max_position_embeddings=UpperCAmelCase     ,   type_vocab_size=UpperCAmelCase     ,   initializer_range=UpperCAmelCase     ,   layer_norm_eps=UpperCAmelCase     ,   pad_token_id=UpperCAmelCase     ,   **UpperCAmelCase     ,   )
  														_lowercase				=	max_ad_position_embeddings
  														_lowercase				=	max_rel_pos
  														_lowercase				=	rel_pos_bins
  														_lowercase				=	fast_qkv
  														_lowercase				=	max_rel_ad_pos
  														_lowercase				=	rel_ad_pos_bins
  														_lowercase				=	convert_sync_batchnorm
  														_lowercase				=	image_feature_pool_shape
  														_lowercase				=	coordinate_size
  														_lowercase				=	shape_size
  														_lowercase				=	has_relative_attention_bias
  														_lowercase				=	has_spatial_attention_bias
  														_lowercase				=	has_visual_segment_embedding
  														_lowercase				=	(
  														    detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
  														)
  
  
  
  							@classmethod
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														return {
  														    "MODEL.MASK_ON": True,
  														    "MODEL.PIXEL_STD": [57.375, 57.120, 58.395],
  														    "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
  														    "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
  														    "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [128], [256], [512]],
  														    "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
  														    "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2000,
  														    "MODEL.RPN.PRE_NMS_TOPK_TEST": 1000,
  														    "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1000,
  														    "MODEL.POST_NMS_TOPK_TEST": 1000,
  														    "MODEL.ROI_HEADS.NAME": "StandardROIHeads",
  														    "MODEL.ROI_HEADS.NUM_CLASSES": 5,
  														    "MODEL.ROI_HEADS.IN_FEATURES": ["p2", "p3", "p4", "p5"],
  														    "MODEL.ROI_BOX_HEAD.NAME": "FastRCNNConvFCHead",
  														    "MODEL.ROI_BOX_HEAD.NUM_FC": 2,
  														    "MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION": 14,
  														    "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead",
  														    "MODEL.ROI_MASK_HEAD.NUM_CONV": 4,
  														    "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7,
  														    "MODEL.RESNETS.DEPTH": 101,
  														    "MODEL.RESNETS.SIZES": [[32], [64], [128], [256], [512]],
  														    "MODEL.RESNETS.ASPECT_RATIOS": [[0.5, 1.0, 2.0]],
  														    "MODEL.RESNETS.OUT_FEATURES": ["res2", "res3", "res4", "res5"],
  														    "MODEL.RESNETS.NUM_GROUPS": 32,
  														    "MODEL.RESNETS.WIDTH_PER_GROUP": 8,
  														    "MODEL.RESNETS.STRIDE_IN_1X1": False,
  														}
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	detectrona.config.get_cfg()
  														for k, v in self.detectrona_config_args.items():
  																					_lowercase				=	k.split("""."""  )
  																					_lowercase				=	detectrona_config
  																					for attribute in attributes[:-1]:
  																												_lowercase				=	getattr(UpperCAmelCase     ,   UpperCAmelCase  )
  																					setattr(UpperCAmelCase     ,   attributes[-1]     ,   UpperCAmelCase  )
  
  														return detectrona_config
  
  
  
style_context: import warnings
  
  from ...utils import logging
  from .image_processing_mobilenet_va import MobileNetVaImageProcessor
  
  
  A_:      Tuple        =			logging.get_logger(__name__)
  
  
  class _lowercase					(       _UpperCAmelCase						):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  							def __init__(    self     ,   *UpperCAmelCase     ,   **UpperCAmelCase  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														warnings.warn(
  														    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
  														    """ Please use MobileNetV2ImageProcessor instead."""     ,   UpperCAmelCase     ,   )
  														super().__init__(*UpperCAmelCase     ,   **UpperCAmelCase  )
  
  
  