I have a weight tensor(64,3, 3, 3) and a scale tensor(64), how to multiply a scale to per filter, a slow solution is showed below:

for i in range(weight.shape[0]): weight[i] = weight[i] * scale[i]

can boradcasting apply to this? please help me out, tks!

This should work:

q = torch.randn(64,3,3,3) t = torch.randn(64) qq = t.unsqueeze(1).unsqueeze(1).unsqueeze(1) * q for i in range(64): torch.allclose(t[i] * q[i], qq[i]) # should be true all the time

This should work: weight = weight* scale.unsqueeze(dim=1).unsqueeze(dim=1).unsqueeze(dim=1) or weight = weight* scale.view(-1, 1, 1, 1) etc.

It works! thanks a lot.