What is dv, dk here?
We now formally describe our proposed Attention Augmentation method.
We use the following naming conventions: H, W and Fin refer to the height, 
width and number
of input filters of an activation map. Nh, dv and dk respectively refer the 
number of heads, the depth of values and the
depth of queries and keys in multihead-attention (MHA).
We further assume that Nh divides dv and dk evenly and
denote dhv and dhk the depth of values and queries/keys per
attention head.

if I do nn.MultiheadAttention(28, 2), then Nh = 2, but, dv, dk, dhv, dhk = ???
If I want to transform an image to another image, then
transformer_model = nn.Transformer(img_size, n_heads)
transformer_model(source_image, target_image)

is this the correct way to use nn.Transformer for images?