GradCAM for Dual Attention ViT

[tayyabapucit]

How can I use Grad CAM for Dual Attention ViT Transformer (davit_tiny.msft_in1k).
I tried to use reshape transform with height,width 7,7 and 14,14
I need to figure out which layer to use or how to reshape the output.

I've successfully used GradCAM, EigenCAM, and ScoreCAM with ResNet, DenseNets, VGG, ViT, and SwinVit. Results are amazing for all these models.

Any Help?

[tayyabapucit]

Ok, I've figured it out.
It worked with
target_layers = [list(model.backbone.modules())[-13]]

and

def reshape_transform2(tensor, height=7, width=7):

result = tensor.reshape(tensor.size(0),
    height, width, tensor.size(2))

# ??Bring the channels to the first dimension,
# like in CNNs.
result = result.transpose(2, 3).transpose(1, 2)

return result

Am I doint it right.?