ydwen
commented
1 year ago Hey microvnn,
You can try wrapping the model to DDP before loading the parameters.
example: ddp_model = DDP(model, device_ids=[rank])
Open microvnn opened 1 year ago
ydwen
commented
1 year ago Hey microvnn,
You can try wrapping the model to DDP before loading the parameters.
example: ddp_model = DDP(model, device_ids=[rank])
sys.path.append('./vendors/Sphereface') config_path = os.path.join('./vendors', 'Sphereface', '20220428_232053', 'config.yml') with open(config_path, 'r') as f: test_config = yaml.load(f, yaml.SafeLoader)
build model
bkb_net = build_from_cfg( test_config['model']['backbone']['net'], 'model.backbone', ) bkb_net.eval() checkpoint = os.path.join('./vendors', 'Sphereface', '20220428_232053', 'models', 'backbone_80000.pth') state_dict = torch.load(checkpoint, map_location=torch.device('cpu')) bkb_net.load_state_dict(state_dict) print(bkb_net)
Please help me.
Result: RuntimeError: Error(s) in loading state_dict for SFNet_deprecated: Missing key(s) in state_dict: "layer1.0.conv1.weight", "layer1.0.conv1.bias", "layer1.1.conv1.weight", "layer1.1.conv1.bias", "layer1.1.conv2.weight", "layer1.1.conv2.bias", "layer2.0.conv1.weight", "layer2.0.conv1.bias", "layer2.1.conv1.weight", "layer2.1.conv1.bias", "layer2.1.conv2.weight", "layer2.1.conv2.bias", "layer2.2.conv1.weight", "layer2.2.conv1.bias", "layer2.2.conv2.weight", "layer2.2.conv2.bias", "layer3.0.conv1.weight", "layer3.0.conv1.bias", "layer3.1.conv1.weight", "layer3.1.conv1.bias", "layer3.1.conv2.weight", "layer3.1.conv2.bias", "layer3.2.conv1.weight", "layer3.2.conv1.bias", "layer3.2.conv2.weight", "layer3.2.conv2.bias", "layer3.3.conv1.weight", "layer3.3.conv1.bias", "layer3.3.conv2.weight", "layer3.3.conv2.bias", "layer3.4.conv1.weight", "layer3.4.conv1.bias", "layer3.4.conv2.weight", "layer3.4.conv2.bias", "layer4.0.conv1.weight", "layer4.0.conv1.bias", "layer4.1.conv1.weight", "layer4.1.conv1.bias", "layer4.1.conv2.weight", "layer4.1.conv2.bias", "fc.weight", "fc.bias". Unexpected key(s) in state_dict: "module.layer1.0.conv1.weight", "module.layer1.0.conv1.bias", "module.layer1.1.conv1.weight", "module.layer1.1.conv1.bias", "module.layer1.1.conv2.weight", "module.layer1.1.conv2.bias", "module.layer2.0.conv1.weight", "module.layer2.0.conv1.bias", "module.layer2.1.conv1.weight", "module.layer2.1.conv1.bias", "module.layer2.1.conv2.weight", "module.layer2.1.conv2.bias", "module.layer2.2.conv1.weight", "module.layer2.2.conv1.bias", "module.layer2.2.conv2.weight", "module.layer2.2.conv2.bias", "module.layer3.0.conv1.weight", "module.layer3.0.conv1.bias", "module.layer3.1.conv1.weight", "module.layer3.1.conv1.bias", "module.layer3.1.conv2.weight", "module.layer3.1.conv2.bias", "module.layer3.2.conv1.weight", "module.layer3.2.conv1.bias", "module.layer3.2.conv2.weight", "module.layer3.2.conv2.bias", "module.layer3.3.conv1.weight", "module.layer3.3.conv1.bias", "module.layer3.3.conv2.weight", "module.layer3.3.conv2.bias", "module.layer3.4.conv1.weight", "module.layer3.4.conv1.bias", "module.layer3.4.conv2.weight", "module.layer3.4.conv2.bias", "module.layer4.0.conv1.weight", "module.layer4.0.conv1.bias", "module.layer4.1.conv1.weight", "module.layer4.1.conv1.bias", "module.layer4.1.conv2.weight", "module.layer4.1.conv2.bias", "module.fc.weight", "module.fc.bias".