code: def _one_step_forward_lm(
      self, decoder_input_ids=None, lm_mems_list=None, pos=0
  ):
      input_mask = mask_padded_tokens(
          decoder_input_ids, self.pad
      ).float()
      lm_hidden_states = self.language_model.encoder.embedding.forward(
          decoder_input_ids, start_pos=pos
      )
      lm_mems_list = self.language_model.encoder.encoder.forward(
          lm_hidden_states,
          input_mask,
          lm_mems_list,
          return_mems=True,
      )
      lm_log_probs = self.language_model.log_softmax.forward(
          hidden_states=lm_mems_list[-1][:, -1:]
      )
      return lm_log_probs, lm_mems_list
  
imports: from contextlib import contextmanager
  import torch
  from nemo.collections.common.parts import NEG_INF, mask_padded_tokens
label_desc: Use image node_id 3 for calling the EnsembleBeamSearchSequenceGenerator obj's underlying member method code with example usage: obj._one_step_forward_lm(decoder_input_ids, lm_mems_list, pos) and returns: lm_log_probs,  lm_mems_list