code: def forward(self, img):
      x = self.conv_embedding(img)
  
      x = self.backbone(x)
  
      x = self.pool(x)
  
      out = self.mlp_head(x)
      distill = self.distill_head(x)
  
      if exists(distill):
          return out, distill
  
      return out
  
imports: from math import ceil
  import torch
  from torch import nn, einsum
  import torch.nn.functional
  from einops import rearrange, repeat
  from einops.layers.torch import Rearrange
label_desc: Use image node_id 2 for calling the LeViT obj's underlying member method code with example usage: obj.forward(img) and returns: out, out,  distill