code: def forward(
      self, x, shared_rel_pos_bias: Optional[torch.Tensor] = None
  ):
      if self.gamma_1 is None:
          x = x + self.drop_path1(
              self.attn(
                  self.norm1(x), shared_rel_pos_bias=shared_rel_pos_bias
              )
          )
          x = x + self.drop_path2(self.mlp(self.norm2(x)))
      else:
          x = x + self.drop_path1(
              self.gamma_1
              * self.attn(
                  self.norm1(x), shared_rel_pos_bias=shared_rel_pos_bias
              )
          )
          x = x + self.drop_path2(
              self.gamma_2 * self.mlp(self.norm2(x))
          )
      return x
  
imports: import math
  from typing import Callable, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.checkpoint import checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, SwiGLU, LayerNorm, DropPath, trunc_normal_, use_fused_attn
  from timm.layers import resample_patch_embed, resample_abs_pos_embed, resize_rel_pos_bias_table
  from ._builder import build_model_with_cfg
  from ._registry import generate_default_cfgs, register_model
  from .vision_transformer import checkpoint_filter_fn
label_desc: Use image node_id 2 for calling the Block obj's underlying member method code with example usage: obj.forward(x, shared_rel_pos_bias) and returns: x