Hello,
The masked_select function allows me to extract elements from a tensor. Given a tensor A and a boolean mask mask, masked_select will give me the indexed elements as a 1D-vector (call it b), such that

b = torch.masked_select(A, mask)

My question is if there is an efficient way would be to achieve the inverse operation? This is, given both b and mask, how can I recover A or rather a version of A where the indexed elements are in the right position and all-non indexed elements of A can be some constant, e.g. zero.
My use case is that A is about 15k x 15k dimensions and b holds about `200k elements. So I need something fast that should also work with auto-grad. When I am implementing a simple for loop, it takes ages to propagate back through the graph.