code: def __init__(
      self,
      vocab_size=30522,
      hidden_size=768,
      num_hidden_layers=12,
      num_attention_heads=12,
      intermediate_size=3072,
      hidden_act="gelu",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      max_position_embeddings=512,
      type_vocab_size=2,
      initializer_range=0.02,
      layer_norm_eps=1e-12,
      pad_token_id=0,
      dim_bbox=8,
      bbox_scale=100.0,
      n_relations=1,
      classifier_dropout_prob=0.1,
      **kwargs,
  ):
      super().__init__(
          vocab_size=vocab_size,
          hidden_size=hidden_size,
          num_hidden_layers=num_hidden_layers,
          num_attention_heads=num_attention_heads,
          intermediate_size=intermediate_size,
          hidden_act=hidden_act,
          hidden_dropout_prob=hidden_dropout_prob,
          attention_probs_dropout_prob=attention_probs_dropout_prob,
          max_position_embeddings=max_position_embeddings,
          type_vocab_size=type_vocab_size,
          initializer_range=initializer_range,
          layer_norm_eps=layer_norm_eps,
          pad_token_id=pad_token_id,
          **kwargs,
      )
  
      self.dim_bbox = dim_bbox
      self.bbox_scale = bbox_scale
      self.n_relations = n_relations
      self.dim_bbox_sinusoid_emb_2d = self.hidden_size // 4
      self.dim_bbox_sinusoid_emb_1d = (
          self.dim_bbox_sinusoid_emb_2d // self.dim_bbox
      )
      self.dim_bbox_projection = (
          self.hidden_size // self.num_attention_heads
      )
      self.classifier_dropout_prob = classifier_dropout_prob
  
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new BrosConfig object from inherited base classes: PretrainedConfig with example: obj = BrosConfig(vocab_size, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, max_position_embeddings, type_vocab_size, initializer_range, layer_norm_eps, pad_token_id, dim_bbox, bbox_scale, n_relations, classifier_dropout_prob)