add large model stable training fix and contrastive loss update for variable seq
# What does this PR do ?

This PR brings two updates:
* Fix SSL contrastive loss to support loss computation for variable input length rather than computation based on subsampling factor
* Add an option to remove bias from Linear and Conv layers in Conformer layers to support scaling for multi billion parameter training [tested currently for 1B parameter using bf16] 

**Collection**: ASR

# Changelog 
- Updated ssl_loss 
- Added argument for conformerlayer to optionally remove bias, default is False


# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [x] New Feature
- [x] Bugfix
- [ ] Documentation 