code: def forward(self, x, rel_pos_bias=None):
      if self.gamma_1 is None:
          x = x + self.drop_path(
              self.attn(self.norm1(x), rel_pos_bias=rel_pos_bias)
          )
          x = x + self.drop_path(self.mlp(self.norm2(x)))
      else:
          x = x + self.drop_path(
              self.gamma_1
              * self.attn(self.norm1(x), rel_pos_bias=rel_pos_bias)
          )
          x = x + self.drop_path(self.gamma_2 * self.mlp(self.norm2(x)))
      return x
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from timm.models.layers import drop_path, to_2tuple, trunc_normal_
  from timm.models.registry import register_model
  from lavis.common.dist_utils import download_cached_file
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.forward(x, rel_pos_bias) and returns: x