class_docstr: CoaT class. 
class_docstr_tok: ["CoaT","class","."]
code: def forward(self, x) -> torch.Tensor:
      if not torch.jit.is_scripting() and self.return_interm_layers:
          # Return intermediate features (for down-stream tasks).
          return self.forward_features(x)
      else:
          # Return features for classification.
          x_feat = self.forward_features(x)
          x = self.forward_head(x_feat)
          return x
  
imports: from functools import partial
  from typing import Tuple, List, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, DropPath, to_2tuple, trunc_normal_, _assert, LayerNorm
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 10 for calling the CoaT obj's underlying member method code with example usage: obj.forward(x) and returns: self, x