code: def __init__(
      self,
      vocab_size=30522,
      hidden_size=768,
      num_attention_heads=12,
      num_qa_labels=9500,
      num_object_labels=1600,
      num_attr_labels=400,
      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,
      l_layers=9,
      x_layers=5,
      r_layers=5,
      visual_feat_dim=2048,
      visual_pos_dim=4,
      visual_loss_normalizer=6.67,
      task_matched=True,
      task_mask_lm=True,
      task_obj_predict=True,
      task_qa=True,
      visual_obj_loss=True,
      visual_attr_loss=True,
      visual_feat_loss=True,
      **kwargs,
  ):
      self.vocab_size = vocab_size
      self.hidden_size = hidden_size
      self.num_attention_heads = num_attention_heads
      self.hidden_act = hidden_act
      self.intermediate_size = intermediate_size
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.max_position_embeddings = max_position_embeddings
      self.type_vocab_size = type_vocab_size
      self.initializer_range = initializer_range
      self.layer_norm_eps = layer_norm_eps
      self.num_qa_labels = num_qa_labels
      self.num_object_labels = num_object_labels
      self.num_attr_labels = num_attr_labels
      self.l_layers = l_layers
      self.x_layers = x_layers
      self.r_layers = r_layers
      self.visual_feat_dim = visual_feat_dim
      self.visual_pos_dim = visual_pos_dim
      self.visual_loss_normalizer = visual_loss_normalizer
      self.task_matched = task_matched
      self.task_mask_lm = task_mask_lm
      self.task_obj_predict = task_obj_predict
      self.task_qa = task_qa
      self.visual_obj_loss = visual_obj_loss
      self.visual_attr_loss = visual_attr_loss
      self.visual_feat_loss = visual_feat_loss
      self.num_hidden_layers = {
          "vision": r_layers,
          "cross_encoder": x_layers,
          "language": l_layers,
      }
      super().__init__(**kwargs)
  
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new LxmertConfig object from inherited base classes: PretrainedConfig with example: obj = LxmertConfig(vocab_size, hidden_size, num_attention_heads, num_qa_labels, num_object_labels, num_attr_labels, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, max_position_embeddings, type_vocab_size, initializer_range, layer_norm_eps, l_layers, x_layers, r_layers, visual_feat_dim, visual_pos_dim, visual_loss_normalizer, task_matched, task_mask_lm, task_obj_predict, task_qa, visual_obj_loss, visual_attr_loss, visual_feat_loss)