class_docstr: <a id="ClassificationHead"></a>
  
  ## MLP Classification Head
  
  This is the two layer MLP head to classify the image based on `[CLS]` token embedding.
class_docstr_tok: ["<","a","id=","''","ClassificationHead","''",">","<","\/a",">","#","#","MLP","Classification","Head","This","is","the","two","layer","MLP","head","to","classify","the","image","based","on","`","[","CLS","]","`","token","embedding","."]
docstr: * `x` is the transformer encoding for `[CLS]` token
docstr_tok: ["*","`","x","`","is","the","transformer","encoding","for","`","[","CLS","]","`","token"]
code: def forward(self, x: torch.Tensor):
      """
      * `x` is the transformer encoding for `[CLS]` token
      """
      # First layer and activation
      x = self.act(self.linear1(x))
      # Second layer
      x = self.linear2(x)
  
      #
      return x
  
imports: import torch
  from torch import nn
  from labml_helpers.module import Module
  from labml_nn.transformers import TransformerLayer
  from labml_nn.utils import clone_module_list
label_desc: Use image node_id 2 for calling the ClassificationHead obj's underlying member method code with example usage: obj.forward(x) and returns: x