code: def _get_features(
      self,
      input_ids=None,
      attention_mask=None,
      token_type_ids=None,
      position_ids=None,
      head_mask=None,
      inputs_embeds=None,
  ):
      outputs = self.bert(
          input_ids,
          attention_mask=attention_mask,
          token_type_ids=token_type_ids,
          position_ids=position_ids,
          head_mask=head_mask,
          inputs_embeds=inputs_embeds,
      )
  
      sequence_output = outputs[0]
  
      sequence_output = self.dropout(sequence_output)
      feats = self.classifier(sequence_output)
      return feats, outputs
  
file_path: DeepKE/src/deepke/event_extraction/standard/bertcrf/bert_crf.py
imports: import logging
  from transformers.models.bert import BertModel, BertPreTrainedModel, BertConfig
  from .crf import *
  from .utils_ee import to_crf_pad, unpad_crf
label_desc: Use image node_id 2 for calling the BertCRFForTokenClassification obj's underlying member method code with example usage: obj._get_features(input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds) and returns: feats,  outputs