Adding RNN encoder for LSTM-Transducer and LSTM-CTC models
# What does this PR do ?

This PR adds RNN-based encoder to NeMo. It enables us to have LSTM-Transducer (RNN-T) and LSTM-CTC models. 

# Changelog 
- Added RNN encoder for ASR models (LSTM-T and LSTM-CTC models)
- Added stacking downsampling
- Added support for proj_size to Transducer decoders
- Added skip_nan_grad support for ASR models which skips the gradients when there is a nan or inf in the gradients

# Usage

```python
# Add a code snippet demonstrating how to use this 
```

**PR Type**:
- [x ] New Feature
- [ ] Bugfix
- [ ] Documentation
