When we use stride, say stride 2, it will pick the 0th, 2nd and so on, is there a way to instead pick 1st, 3rd and so on.
Is there a parameter to conv1d or any other way that will help me get with stride 2 same results as
F.conv1d(t_input, t_weight, padding=5, stride=1)[0,0,1:10:2]

Actual Stride invocation that I am using
F.conv1d(t_input, t_weight, padding=5, stride=2)[0,0,0:5]

The default result that I get is same as
F.conv1d(t_input, t_weight, padding=5, stride=1)[0,0,0:10:2]

I am porting a TF model and somehow the conv there seems to be picking the 1::2 element and torch seems to be picking 0::2. Wanted both model implementations to give same result.