docstr: Run encoder and normalize emissions
code: def get_emissions(self, models, encoder_input):
      """Run encoder and normalize emissions"""
      model = models[0]
      encoder_out = model(**encoder_input)
      if hasattr(model, "get_logits"):
          emissions = model.get_logits(
              encoder_out
          )  # no need to normalize emissions
      else:
          emissions = model.get_normalized_probs(
              encoder_out, log_probs=True
          )
      return emissions.transpose(0, 1).float().cpu().contiguous()
  
imports: import gc
  import itertools
  import os.path
  from typing import List
  import warnings
  from collections import deque, namedtuple
  import numpy
  import torch
  from examples.speech_recognition.data.replabels import unpack_replabels
  from fairseq import tasks
  from fairseq.utils import apply_to_sample
  from omegaconf import open_dict
  from fairseq.dataclass.utils import convert_namespace_to_omegaconf
label_desc: Use image node_id 3 for calling the W2lDecoder obj's underlying member method code with example usage: obj.get_emissions(models, encoder_input) and returns: emissions