code: def forward(self, img):
      b, _, h, w, p = *img.shape, self.patch_size
  
      x = self.to_patch_embedding(img)
      n = x.shape[1]
  
      cls_tokens = repeat(self.cls_token, "() n d -> b n d", b=b)
      x = torch.cat((cls_tokens, x), dim=1)
  
      fmap_dims = {"h": h // p, "w": w // p}
      x = self.transformer(x, fmap_dims=fmap_dims)
  
      return self.mlp_head(x[:, 0])
  
imports: from math import sqrt, pi, log
  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 RvT obj's underlying member method code with example usage: obj.forward(img) and returns: self