class_docstr: BERT pooler layer.
  Based on: BERT (pytorch-transformer)
  https://github.com/huggingface/transformers
code: def forward(self, hidden_states):
      first_token_tensor = hidden_states[:, 0]
      pooled_output = self.dense(first_token_tensor)
      pooled_output = self.activation(pooled_output)
      return pooled_output
  
imports: from __future__ import annotations
  import math
  from collections.abc import Sequence
  import torch
  from torch import nn
  from monai.config.type_definitions import PathLike
  from monai.utils import optional_import
label_desc: Use image node_id 2 for calling the Pooler obj's underlying member method code with example usage: obj.forward(hidden_states) and returns: pooled_output