Are you attempting to do fine-tuning or something else like transfer learning ?
Meanwhile I saw this tutorial but the source code link gives me a 404
https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html 21
Here is how I freeze a pre-trained model to do what is now called transfer learning… and I erase the last fc layer
if model_conf["hyperParameters"]["freeze_pretrained_gradients"]:
            print("Using backbone as fixed feature extractor")
            modules = list(backbone_nn.children())[:-1]  # delete the last fc layer.
            backbone_nn = nn.Sequential(*modules)

            # FasterRCNN needs to know the number of
            # output channels in a backbone. For resnet101, it's 2048
            for param in backbone_nn.parameters():
                param.requires_grad = False
            backbone_nn.out_channels = 2048

the key is that .children() call