In MegatronGPTModels, Creation of AutoCastTransformerLayer with TransformerEngine ignores chosen activation 
**Describe the bug**

I was training a MegatronGPTModel using `megatron_gpt_pretraining.py` and a machine with H100 chips. When I set `transformer_engine=true` I later noticed that my requested `activation=fast-swiglu` was ignored. 

I traced the issue back to the [transformer.py](./nemo/collections/nlp/modules/common/megatron/transformer.py) file, in the definition of the class `AutocastTransformerLayer`. In the initializer there is no `activation` parameter being accepted or passed into the layer. 

**Steps/Code to reproduce bug**

python megatron_gpt_pretraining.py model.activation=swiglu

**Expected behavior**

The model to use the SwiGLU activation function, which can be seen by the `layernorm_mlp.fc1_weight` parameter (or `mlp.dense_h_to_4h` in the non transformer_engine code) being of dimension `2 * config.ffn_hidden_size` .

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

 - Environment location: [Docker]
 - Method of NeMo install: [from source]. Please specify exact commands you used to install.

```bash
git clone https://github.com/NVIDIA/NeMo.git
DOCKER_BUILDKIT=1 docker build -f Dockerfile -t nemo:latest .
```
