Decoding hangs with pretrained models (conformer transducer, contextnet)
**Describe the bug**

The decoding hangs with some pretrained models, no error, it just freezes at some point. Killing the process, re-running the same command gets the same behavior.
I have observed it with different models on different data: `stt_en_conformer_tranducer_large.nemo`, `stt_en_contextnet_256.nemo`.

**Steps/Code to reproduce bug**

```bash
python examples/asr/transcribe_speech.py \ model_path=models/downloaded/conformer_transducer/stt_en_conformer_transducer_medium.nemo \
dataset_manifest=some_data_to_transcribe.json \
batch_size=2  \
output_filename=transcription_nemo_conformer_transducer_medium.json
```
The resulting end of the log is something like the following:

```
Transcribing:   0%|          | 0/65903 [00:00<?, ?it/s][NeMo W 2021-10-20 09:26:58 patch_utils:49] torch.stft() signature has been updated for PyTorch 1.7+
    Please update PyTorch to remain compatible with later versions of NeMo.
Transcribing:  33%|███▎      | 21583/65903 [30:25<52:12, 14.15it/s]
```
and at every trial, the step where it gets stuck is the same. Looking at the data in that batch (assuming batches are read in the order of the json input file) there is nothing specific and removing some files from the json list does not help. So maybe nemo reshuffles the order of files to be decoded?

Is there a way to get more detailed logs of why the freeze may happen?

**Environment overview (please complete the following information)**

- installed with conda
- version 1.4.0

**Additional context**
GPU model: RTX 3090
