How can I export titanet-l model to onnx?
Hello, I have exported the marblenet vad model to onnx using the https://github.com/NVIDIA/NeMo/blob/stable/tutorials/asr/Online_Offline_Microphone_VAD_Demo.ipynb tutorial. 

Unfortunately, when I try to replicate the steps for the titanet model in the _extract_embeddings function, but it doesn't work.


Is there a tutorial about exporting the speaker model to onnx, or is it possible to export ?

```
    def _extract_embeddings(self, manifest_file: str, scale_idx: int, num_scales: int):
        """
        This method extracts speaker embeddings from segments passed through manifest_file
        Optionally you may save the intermediate speaker embeddings for debugging or any use. 
        """
        self._setup_spkr_test_data(manifest_file)
        self.embeddings = {}
        self._speaker_model = self._speaker_model.to(self._device)
        self._speaker_model.eval()
        self.time_stamps = {}
        
        self.speaker_model.export('titanet_l.onnx')
        ort_session = onnxruntime.InferenceSession('titanet_l.onnx')
        
        all_embs = torch.empty([0])
        for test_batch in tqdm(self._speaker_model.test_dataloader(), desc=f'[{scale_idx+1}/{num_scales}] extract embeddings',leave=True):
            test_batch = [x.to(self._device) for x in test_batch]
            processed_signal, processed_signal_len = self.speaker_model.preprocessor(input_signal=test_batch[0],length=test_batch[1])
            with autocast():
                
                #_, embs = self._speaker_model.forward(input_signal=test_batch[0], input_signal_length=test_batch[1])
                ort_inputs = {ort_session.get_inputs()[0].name: to_numpy(processed_signal), }
                _,ologits = ort_session.run(None, ort_inputs)
                alogits = np.asarray(ologits)
                logits = torch.from_numpy(alogits[0])
                emb_shape = ologits.shape[-1]
                embs = embs.view(-1, emb_shape)
                all_embs = torch.cat((all_embs, embs.cpu().detach()), dim=0)
                
            del test_batch```

```[tasklist]
### Tasks
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