code: def forward(self, x):
      x = x + self.drop_path(self.attn(self.norm1(x)))
      x = x + self.drop_path(self.mlp(self.norm2(x)))
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from timm.models.layers import DropPath
  from lavis.models.ulip_models.pointbert.dvae import Group
  from lavis.models.ulip_models.pointbert.dvae import Encoder
  from lavis.models.ulip_models.pointbert.logger import print_log
  from lavis.models.ulip_models.pointbert.checkpoint import get_missing_parameters_message, get_unexpected_parameters_message
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.forward(x) and returns: x