I don’t think this is how multi head attention pooling works. I suggest you read the paper and pytorch docu carefully.
The conv1d in your first post will result in parameter sharing and the second will cause incorrect output feature computation.
Furthermore, if you are really into this problem, I also strongly recommend you read the code in my previous reply, which I think might be what you actually have in mind.