Depending how much has changed in your custom Resnet implementation, you could either try to directly load the pretrained resnet state_dict with the strict=False option:
resnet_adapted = MyResnet()
pretrained = torchvision.models.resnet50(pretrained=True)
resnet_adapted.load_state_dict(pretrained.state_dict(), strict=False)

or load specific layers manually by iterating the keys in the pretrained state_dict.
Why do you think you cannot freeze specific layers in your model? Are you seeing any errors?