A pass-through layer (ReLU) and conv (1x1, stride 1, pad 0) both do identity mapping.
(self)
| 53 | self.assertEquals(b, -1) |
| 54 | |
| 55 | def test_pass(self): |
| 56 | """ |
| 57 | A pass-through layer (ReLU) and conv (1x1, stride 1, pad 0) |
| 58 | both do identity mapping. |
| 59 | """ |
| 60 | n = coord_net_spec() |
| 61 | ax, a, b = coord_map_from_to(n.deconv, n.data) |
| 62 | n.relu = L.ReLU(n.deconv) |
| 63 | n.conv1x1 = L.Convolution( |
| 64 | n.relu, num_output=10, kernel_size=1, stride=1, pad=0) |
| 65 | for top in [n.relu, n.conv1x1]: |
| 66 | ax_pass, a_pass, b_pass = coord_map_from_to(top, n.data) |
| 67 | self.assertEquals(ax, ax_pass) |
| 68 | self.assertEquals(a, a_pass) |
| 69 | self.assertEquals(b, b_pass) |
| 70 | |
| 71 | def test_padding(self): |
| 72 | """ |
nothing calls this directly
no test coverage detected