class_docstr: BERT output layer.
  Based on: BERT (pytorch-transformer)
  https://github.com/huggingface/transformers
code: def forward(self, hidden_states, input_tensor):
      hidden_states = self.dense(hidden_states)
      hidden_states = self.dropout(hidden_states)
      hidden_states = self.LayerNorm(hidden_states + input_tensor)
      return hidden_states
  
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 BertOutput obj's underlying member method code with example usage: obj.forward(hidden_states, input_tensor) and returns: hidden_states