code: def forward(self, hidden_states, attention_mask, sequence_lengths):
      hidden_states = self.encoders.forward(
          hidden_states, sequence_lengths
      )
      return (hidden_states,)
  
imports: from typing import List, Optional
  from loguru import logger
  from nebullvm.optional_modules.torch import torch, torch_distributed
  from nebullvm.optional_modules.huggingface import BertConfig, BertEmbeddings, BertEncoder, BertPooler, BertPreTrainedModel
  from .checkpoint_quantization import checkpoint_quantization
label_desc: Use image node_id 2 for calling the CustomEncoder obj's underlying member method code with example usage: obj.forward(hidden_states, attention_mask, sequence_lengths) and returns: hidden_states