class_docstr: Class Attention Layer as in CaiT https://arxiv.org/abs/2103.17239
class_docstr_tok: ["Class","Attention","Layer","as","in","CaiT","https",":","\/\/arxiv.org\/abs\/2103.17239"]
code: def forward(self, x):
      B, N, C = x.shape
      qkv = self.qkv(x).reshape(
          B, N, 3, self.num_heads, C // self.num_heads
      )
      qkv = qkv.permute(2, 0, 3, 1, 4)
      q, k, v = (
          qkv[0],
          qkv[1],
          qkv[2],
      )  # make torchscript happy (cannot use tensor as tuple)
  
      qc = q[:, :, 0:1]  # CLS token
      attn_cls = (qc * k).sum(dim=-1) * self.scale
      attn_cls = attn_cls.softmax(dim=-1)
      attn_cls = self.attn_drop(attn_cls)
  
      cls_tkn = (
          (attn_cls.unsqueeze(2) @ v).transpose(1, 2).reshape(B, 1, C)
      )
      cls_tkn = self.proj(cls_tkn)
      x = torch.cat([self.proj_drop(cls_tkn), x[:, 1:]], dim=1)
      return x
  
imports: import logging
  import math
  from functools import partial
  from typing import List, Optional
  import torch
  import torch.nn
  from fairscale.nn import checkpoint_wrapper
  from vissl.config import AttrDict
  from vissl.models.model_helpers import DropPath, to_2tuple, trunc_normal_
  from vissl.models.trunks import register_model_trunk
  from vissl.models.trunks.vision_transformer import Mlp
  from vissl.utils.fsdp_utils import fsdp_wrapper
  from vissl.utils.misc import set_torch_seed
label_desc: Use image node_id 2 for calling the ClassAttention obj's underlying member method code with example usage: obj.forward(x) and returns: x