[Bug] RoPE positional embedding doesn't work when sequence_parallel is enabled for GPT models
**Describe the bug**

When enabling `rope` position_embedding_type and  `sequence_parallel` in NeMo GPT pretraining, the training will give runtime error: 

```
  File "/workspace/NeMo/nemo/collections/nlp/modules/common/megatron/rotary_pos_embedding.py", line 59, in apply_rotary_pos_emb
    t = (t * freqs.cos()) + (_rotate_half(t) * freqs.sin())
RuntimeError: The size of tensor a (2048) must match the size of tensor b (1024) at non-singleton dimension 0
```

**Steps/Code to reproduce bug**

Follow the [tutorial](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/nlp/nemo_megatron/gpt/gpt_training.html) to train GPT model with `model.position_embedding_type=rope` and `model.sequence_parallel=True`

**Expected behavior**

Expect there will be no runtime error when both options are enabled. 

**Environment overview (please complete the following information)**

 - Environment location: [Bare-metal, Docker, Cloud(specify cloud provider - AWS, Azure, GCP, Collab)]
 - Method of NeMo install: [pip install or from source]. Please specify exact commands you used to install.
 - If method of install is [Docker], provide `docker pull` & `docker run` commands used

**Environment details**

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version
- PyTorch version
- Python version

**Additional context**

Add any other context about the problem here.
Example: GPU model
