How to implement Grad-CAM for Mvit and Mvitv2?

I'm planning to train and visualize using Mvit and Mvitv2. Does anyone know how to write the grad-cam section for Mvit and MvitV2?

For reference, this is how it's done for SlowFast:

```bash
MODEL_VIS:
ENABLE: True
# MODEL_WEIGHTS: True # Set to True to visualize model weights.
# ACTIVATIONS: True # Set to True to visualize feature maps.
# INPUT_VIDEO: True # Set to True to visualize the input video(s) for the corresponding feature maps.
# LAYER_LIST: ['s5/pathway1_res2', 's5/pathway0_res2'] # List of layer names to visualize weights and activations for.
GRAD_CAM:
ENABLE: True
LAYER_LIST: ['s5/pathway1_res2', 's5/pathway0_res2'] # List of CNN layers to use for Grad-CAM visualization method.
# The number of layer must be equal to the number of pathway(s).

```