Hybrid Autoregressive Transducer (HAT)
# What does this PR do ?

Add HAT model as a new joint network type (HATJoint) for RNNT model. The difference is only in decoding time -- HAT.joint.joint returns two outputs: hat_logprobs and internal_lm_logprobs (for internal lm subtraction in case of Shallow Fusion with external n-gram LM).

**Collection**: [ASR]

# Usage
* For HAT model training you need replace `_target_: nemo.collections.asr.modules.RNNTJoint` with `_target_: nemo.collections.asr.modules.HATJoint` in `joint` part of standard transducer config.

* For Shallow Fusion with external n-gram LM use RNNT `maes` decoding algorithm which is able to work with HATJoint model.  

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

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation

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# Additional Information
* Related to # (issue)
