Minimal ways to learn with multiple revisits

revisitconv2d.py

# batch, time, bands, height, width
B, T, C, H, W = x.shape
C_o = 32  # hyperparam

F = lambda i, o, g=1:
    nn.Conv2d(in_channels=i,
              out_channels=o,
              kernel_size=3, 
              padding='same',
              groups=g)

# revisit-invariant / shared:
f = F(C, Co)
x = f(x.view(B*T, C, H, W))

# revisit-specific / revisit-wise:
f = F(T*C, T*Co, T)
x = f(x.view(B, T*C, H, W))

# revisit-connected:
f = F(C, Co)
x = f(x)

# in any case
x = x.view(B, T, C_o, H, W)