(self, block, inplanes, planes, blocks, stride=1)
| 638 | return nn.ModuleList(transition_layers) |
| 639 | |
| 640 | def _make_layer(self, block, inplanes, planes, blocks, stride=1): |
| 641 | downsample = None |
| 642 | if stride != 1 or inplanes != planes * block.expansion: |
| 643 | downsample = nn.Sequential( |
| 644 | nn.Conv2d(inplanes, planes * block.expansion, kernel_size=1, stride=stride, bias=False), |
| 645 | nn.BatchNorm2d(planes * block.expansion, momentum=_BN_MOMENTUM), |
| 646 | ) |
| 647 | |
| 648 | layers = [block(inplanes, planes, stride, downsample)] |
| 649 | inplanes = planes * block.expansion |
| 650 | for i in range(1, blocks): |
| 651 | layers.append(block(inplanes, planes)) |
| 652 | |
| 653 | return nn.Sequential(*layers) |
| 654 | |
| 655 | def _make_stage(self, layer_config, num_inchannels, multi_scale_output=True): |
| 656 | num_modules = layer_config['NUM_MODULES'] |
no outgoing calls
no test coverage detected