(num_classes=1000, in_channels=3)
| 10 | return ResNet(ResNetBlock, [3, 4, 6, 3], num_classes, in_channels) |
| 11 | |
| 12 | def ResNet50(num_classes=1000, in_channels=3): |
| 13 | from ..nn.layers import BottleneckBlock |
| 14 | from ..nn.convolution import ResNet |
| 15 | return ResNet(BottleneckBlock, [3, 4, 6, 3], num_classes, in_channels) |