    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()
Run encoder and normalize emissions
examples/speech_recognition/w2l_decoder.py