I was wondering is there any possibility to change a function of a preloaded model, in my case:
model = torchvision.models.detection.retinanet_resnet50_fpn(pretrained=False,
num_classes=len(class_labels))
- I have a predefined RetinaNet model with ResNet50 FPN
- managed to update RetinaNetHead module, adding a new head to the model (custom loss and forward)
- as far as I saw, RetinaNet(nn.Module) has a function called postprocess_detections, which I should modify, to have the detections from the new head
Is it possible to somehow subclass RetinaNet and overwrite that function, given the preloaded model or should I rewrite the whole class, then add FPN backbone?