Hello, my first post here. I did search for the question but wasn’t able to find it elsewhere in the forum.
I have a tensor X of dimension A, and a tensor Y of dimensions MxNxP and want to create a new tensor Z of dimensions MxAxNxP where Z[m,a,n,p] = X[a]*Y[m,n,p].
I did find a solution but was rather inelegant and possibly inefficient.
There is a simple way of doing this?
Broadcasting should work as seen here:
A, M, N, P = 2, 3, 4, 5
X = torch.randn(A)
Y = torch.randn(M, N, P)
Z_ref = torch.zeros(M, A, N, P)
# slow approach to create reference
for m in range(M):
for a in range(A):
for n in range(N):
for p in range(P):
Z_ref[m, a, n, p] = X[a] * Y[m, n, p]
# non-loop approach
Z = X[None, :, None, None] * Y[:, None, ...]
print((Z_ref - Z).abs().max())
Thanks @ptrblck, that is a very nice solution!