Hi everyone,

I would like to implement a layer looking like a fully connected one, but that has less connections. I managed to it (I think), but it seems like it is really slow. Is it possible to do this in a faster way?

Here is the code:

```
import torch
import torch.nn as nn
if __name__ == '__main__':
# random tensor
x = torch.randn(1, 1, 1024)
# create linear layers
size_window = 16
nb_linear_needed = 1024 // size_window
linear_layers = nn.ModuleList()
for i in range(nb_linear_needed):
linear_layers.append(nn.Linear(size_window, size_window // 2))
# pass every part of x through all linear layers
new_x = torch.zeros(x.shape[0], x.shape[1], x.shape[2] // 2).cuda()
for i, linear_layer in enumerate(linear_layers):
new_borne_inf = i * (size_window // 2)
new_borne_sup = new_borne_inf + size_window // 2
borne_inf = i * size_window
borne_sup = borne_inf + size_window
new_x[:, :, new_borne_inf:new_borne_sup] = linear_layer(x[:, :, borne_inf:borne_sup])
print('x shape:', x.shape)
print('new_x shape:', new_x.shape)
exit()
```

Thanks!