This won’t necessarily give the same output.
E.g. if you are using conv layers with some padding, the outputs might differ:
conv = nn.Conv2d(1, 1, 3, 1, 1)
x = torch.randn(1, 1, 6, 6)
output = conv(x)
output_half = conv(x[:, :, 3:, 3:])

print(output[:, :, 3:, 3:] == output_half)
> tensor([[[[0, 0, 0],
            [0, 1, 1],
            [0, 1, 1]]]], dtype=torch.uint8)