add reset learning rate functionality
- Use case 1: `reset_lr=True, reset_lr_steps=False`
We want to reset_lr to init_lr (0 or optim.lr) in order to train it on another data and don't care about learning rate's max number of steps.

- Use case 2: `reset_lr=True, reset_lr_steps=False` 
We want to reset_lr and we also want to reach min_lr by the end of the training by using the same trainer.max_steps as for previous run of this checkpoint. So in this case we want to update lr's max_steps and decay_steps in the next way:
`max_steps = max_steps - consumed_steps,
decay_steps = decay_steps - consumed_steps`
where `conusmed_steps` is the number of steps already completed at the checkpoint.
Example:
![image](https://github.com/NVIDIA/NeMo/assets/37850217/90387f47-f29e-40d4-ac6f-790bb0a265ec)


# What does this PR do ?

Adds reset learning rate functionality.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

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

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# Additional Information
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