class_docstr: Classification Head for  transformer encoders
class_docstr_tok: ["Classification","Head","for","transformer","encoders"]
code: def forward(self, hidden_state):
      # hidden_state = nn.functional.relu(self.mlp1(hidden_state))
      # hidden_state = self.mlp2(hidden_state)
      logits = self.mlp(hidden_state)
      return logits
  
imports: from torch import nn
label_desc: Use image node_id 2 for calling the ClassificationHead obj's underlying member method code with example usage: obj.forward(hidden_state) and returns: logits