(l, ch_out, stride, preact)
| 44 | |
| 45 | |
| 46 | def preact_bottleneck(l, ch_out, stride, preact): |
| 47 | # stride is applied on the second conv, following fb.resnet.torch |
| 48 | l, shortcut = apply_preactivation(l, preact) |
| 49 | l = Conv2D('conv1', l, ch_out, 1, activation=BNReLU) |
| 50 | l = Conv2D('conv2', l, ch_out, 3, strides=stride, activation=BNReLU) |
| 51 | l = Conv2D('conv3', l, ch_out * 4, 1) |
| 52 | return l + resnet_shortcut(shortcut, ch_out * 4, stride) |
| 53 | |
| 54 | |
| 55 | def preact_group(name, l, block_func, features, count, stride): |
nothing calls this directly
no test coverage detected