Torchscripting Transducer model results in " Module 'FilterbankFeatures' has no attribute 'stft' "
```python
from nemo.collections.asr.models import (
    EncDecRNNTModel,
)
import torch.quantization.quantize_fx as quantize_fx

asr_model = EncDecRNNTModel.restore_from(<path>)

asr_model.eval()

quantized_model = torch.quantization.quantize_dynamic(
        asr_model, qconfig_spec={torch.nn.Linear}, dtype=torch.qint8, inplace=True
    )
scripted_model = torch.jit.script(quantized_model)
torch.jit.save(scripted_model, "hindi_medium_rnnt.pt")
 ```
 I am trying to convert a nemo rnnt transducer model to torchscript for testing mobile deployment and the torch.jit.script results in the following error:
 
```
Module 'FilterbankFeatures' has no attribute 'stft' (This function exists as an attribute on the Python module, but we failed to compile it to a TorchScript function.
The error stack is reproduced here:
local variable 'idx' referenced before assignment:
  File "/home/gowtham/anaconda3/envs/android-wsl/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 327
        # disable autocast to get full range of stft values
        with torch.cuda.amp.autocast(enabled=False):
            x = self.stft(x)
                ~~~~~~~~~ <--- HERE

        # torch returns real, imag; so convert to magnitude
```

1. I couldn't find lot of related issues online, so wanted to check if you have recommended ways to convert nemo conformed transducer models to torchscript? 

2. I also tried using [nemo_model.export](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/core/export.html) method  like this:
```python
quantized_model.export(
       "hindi_medium_rnnt.pt", try_script=True, verbose=True
    )
```
^ this also runs into multiple jit.script() failed errors but eventually produces encoder.pt and decoder-joint.pt files which are however not usable with torch.jit.load methods 