Solved by KFrank in post #2 
              
              
                Hi Omer! 

You can .reshape() your input tensor and use the groups constructor 
argument of Conv1d: 
>>> import torch
>>> torch.__version__
'1.9.0'
>>> _ = torch.manual_seed (2021)
>>> b = 2
>>> c = 3
>>> n = 5
>>> m = 2
>>> t = torch.rand ([b, c, n, m])
>>> u = t.permute (0, 3, 1, 2).reshape (b, m …