add feature to drop checkpoint layers
# What does this PR do ?

1. Adds a feature similar to mcore's --skip-train flag.
3. Adds drop-layers feature support.
4. Adds script which loads the ckpt, trims needed layers, and saves trimmed checkpoint.

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

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

# Usage
* Trim the model. Please, note that layer indices start from 1. Llama3 8b model example:
```ubuntu
python -m torch.distributed.launch --nproc_per_node=8 \
     NeMo/examples/nlp/language_modeling/megatron_gpt_drop_layers.py \
     --path_to_nemo /path/to/model.nemo \
     --path_to_save /path/to/save/trimmed_model.nemo \
     --tensor_model_parallel_size 8 \
     --pipeline_model_parallel_size 1 \
     --gpus_per_node 8 \
     --drop_layers 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
```
If you want to save trimmed model in zarr ckpt format (deprecated), add this flag to the command:
```ubuntu
--zarr
```

* Validate the model:
```ubuntu
python NeMo/examples/nlp/language_modeling/megatron_gpt_pretraining.py \
  --config-path=/path/to/folder/with/model/config \
  --config-name=llama3_8b.yaml \
  trainer.limit_val_batches=number_of_batches_in_validation_step \
  model.restore_from_path=/path/to/trimmed_model.nemo \
  model.skip_train=True \
  model.data.data_impl=mock \
  model.data.data_prefix=[]
```
To use specific dataset instead of mock dataset:
```ubuntu
model.data.data_impl=mmap \
model.data.data_prefix=["path/to/datafile1", "path/to/datafile2"]
```

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**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**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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# Additional Information
* Related to # (issue)
