Unable to load WaveGlow checkpoints or models: TypeError: Expected data to be int, Sequence or Mapping, but got NoneType
**Describe the bug**

I can train WaveGlow models, but when I try to load checkpoints or `.nemo` files back, I am not able to.

**Steps/Code to reproduce bug**

Train, in a Google Colab GPU environment with or without Apex, a Waveglow 16khz model for one epoch. When attempting to load it back, either the checkpoint or the `.nemo` archive, I get the following error consistently:

```
  File "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/supporters.py", line 589, in _nested_calc_num_data
    raise TypeError(f"Expected data to be int, Sequence or Mapping, but got {type(data).__name__}")
TypeError: Expected data to be int, Sequence or Mapping, but got NoneType
```

Please list *minimal* steps or code snippet for us to be able to reproduce the bug.

1. Train a new WaveGlow model for one epoch using the defaults, following the example in https://github.com/NVIDIA/NeMo/blob/main/examples/tts/waveglow.py. I have barely altered this, only adding a snippet to restore a model from a file.
2. Use `model = WaveGlowModel.restore_from(path_to_my_model)`. It will fail with the above error. Loading the checkpoint also fails with the same error.


**Expected behavior**

I expect to be able to load either checkpoints or `.nemo` files.
**Environment overview (please complete the following information)**

 - Environment location: colab
 - Method of NeMo install: [pip install or from source]. pip
 
**Environment details**

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version: Ubuntu 18.04 .5 LTS
- PyTorch version: 1.10.0+cu111
- Python version: Python 3.7.12

**Additional context**
I'm not sure if the fact that it's 16khz matters, but it's the only meaningful deviation  have from the example. Some online research suggests that this is because there's some mixed CPU/GPU training going on, but I wasn't able to find much more information than that, or how to fix it.

I will also note, that I expect a `.nemo` file for each checkpoint, and this does not seem to be the behavior - there seems to be just one `.nemo` file and many large `.ckpt` files, but this may be unrelated. 