Open FXMEIa opened 1 year ago
Hello, I would like to ask which model should be used for inference during testing? I am getting some errors while loading the model.
RuntimeError: Error(s) in loading state_dict for IHN: Unexpected key(s) in state_dict: "update_block_4.cnn_weight.layer0.0.weight", "update_block_4.cnn_weight.layer0.0.bias", "update_block_4.cnn_weight.layer0.1.weight", "update_block_4.cnn_weight.layer0.1.bias", "update_block_4.cnn_weight.layer0.3.weight", "update_block_4.cnn_weight.layer0.3.bias", "update_block_4.cnn_weight.layer0.4.weight", "update_block_4.cnn_weight.layer0.4.bias", "update_block_4.cnn_weight.layer1.0.weight", "update_block_4.cnn_weight.layer1.0.bias", "update_block_4.cnn_weight.layer1.1.weight", "update_block_4.cnn_weight.layer1.1.bias", "update_block_4.cnn_weight.layer2.0.weight", "update_block_4.cnn_weight.layer2.0.bias", "update_block_4.cnn_weight.layer2.1.weight", "update_block_4.cnn_weight.layer2.1.bias", "update_block_4.cnn_weight.layer3.0.weight", "update_block_4.cnn_weight.layer3.0.bias", "update_block_4.cnn_weight.layer3.1.weight", "update_block_4.cnn_weight.layer3.1.bias", "update_block_4.cnn_weight.layer4.0.weight", "update_block_4.cnn_weight.layer4.0.bias", "update_block_4.cnn_weight.layer4.1.weight", "update_block_4.cnn_weight.layer4.1.bias", "update_block_4.cnn_weight.layer4_global.0.weight", "update_block_4.cnn_weight.layer4_global.0.bias", "update_block_4.cnn_weight.layer4_global.1.weight", "update_block_4.cnn_weight.layer4_global.1.bias", "update_block_4.cnn_weight.layer5.0.weight", "update_block_4.cnn_weight.layer5.0.bias", "update_block_4.cnn_weight.layer5.1.weight", "update_block_4.cnn_weight.layer5.1.bias", "update_block_4.cnn_weight.layer6.0.weight", "update_block_4.cnn_weight.layer6.0.bias", "update_block_4.cnn_weight.layer6.1.weight", "update_block_4.cnn_weight.layer6.1.bias", "update_block_4.cnn_weight.layer7.0.weight", "update_block_4.cnn_weight.layer7.0.bias", "update_block_4.cnn_weight.layer7.1.weight", "update_block_4.cnn_weight.layer7.1.bias", "update_block_4.cnn_weight.layer8.0.weight", "update_block_4.cnn_weight.layer8.0.bias", "update_block_4.cnn_weight.layer8.1.weight", "update_block_4.cnn_weight.layer8.1.bias", "update_block_4.cnn_weight.layer9.0.weight", "update_block_4.cnn_weight.layer9.0.bias", "update_block_4.cnn_weight.layer10.0.weight", "update_block_4.cnn_weight.layer10.0.bias", "update_block_4.cnn_weight.layer10.1.weight", "update_block_4.cnn_weight.layer10.1.bias", "update_block_4.cnn_weight.layer10.3.weight", "update_block_4.cnn_weight.layer10.3.bias".
Hi, please check if you load the wrong model. For example, you load the model with weight prediction into the code with no weight prediction.
Hello, I would like to ask which model should be used for inference during testing? I am getting some errors while loading the model.
RuntimeError: Error(s) in loading state_dict for IHN: Unexpected key(s) in state_dict: "update_block_4.cnn_weight.layer0.0.weight", "update_block_4.cnn_weight.layer0.0.bias", "update_block_4.cnn_weight.layer0.1.weight", "update_block_4.cnn_weight.layer0.1.bias", "update_block_4.cnn_weight.layer0.3.weight", "update_block_4.cnn_weight.layer0.3.bias", "update_block_4.cnn_weight.layer0.4.weight", "update_block_4.cnn_weight.layer0.4.bias", "update_block_4.cnn_weight.layer1.0.weight", "update_block_4.cnn_weight.layer1.0.bias", "update_block_4.cnn_weight.layer1.1.weight", "update_block_4.cnn_weight.layer1.1.bias", "update_block_4.cnn_weight.layer2.0.weight", "update_block_4.cnn_weight.layer2.0.bias", "update_block_4.cnn_weight.layer2.1.weight", "update_block_4.cnn_weight.layer2.1.bias", "update_block_4.cnn_weight.layer3.0.weight", "update_block_4.cnn_weight.layer3.0.bias", "update_block_4.cnn_weight.layer3.1.weight", "update_block_4.cnn_weight.layer3.1.bias", "update_block_4.cnn_weight.layer4.0.weight", "update_block_4.cnn_weight.layer4.0.bias", "update_block_4.cnn_weight.layer4.1.weight", "update_block_4.cnn_weight.layer4.1.bias", "update_block_4.cnn_weight.layer4_global.0.weight", "update_block_4.cnn_weight.layer4_global.0.bias", "update_block_4.cnn_weight.layer4_global.1.weight", "update_block_4.cnn_weight.layer4_global.1.bias", "update_block_4.cnn_weight.layer5.0.weight", "update_block_4.cnn_weight.layer5.0.bias", "update_block_4.cnn_weight.layer5.1.weight", "update_block_4.cnn_weight.layer5.1.bias", "update_block_4.cnn_weight.layer6.0.weight", "update_block_4.cnn_weight.layer6.0.bias", "update_block_4.cnn_weight.layer6.1.weight", "update_block_4.cnn_weight.layer6.1.bias", "update_block_4.cnn_weight.layer7.0.weight", "update_block_4.cnn_weight.layer7.0.bias", "update_block_4.cnn_weight.layer7.1.weight", "update_block_4.cnn_weight.layer7.1.bias", "update_block_4.cnn_weight.layer8.0.weight", "update_block_4.cnn_weight.layer8.0.bias", "update_block_4.cnn_weight.layer8.1.weight", "update_block_4.cnn_weight.layer8.1.bias", "update_block_4.cnn_weight.layer9.0.weight", "update_block_4.cnn_weight.layer9.0.bias", "update_block_4.cnn_weight.layer10.0.weight", "update_block_4.cnn_weight.layer10.0.bias", "update_block_4.cnn_weight.layer10.1.weight", "update_block_4.cnn_weight.layer10.1.bias", "update_block_4.cnn_weight.layer10.3.weight", "update_block_4.cnn_weight.layer10.3.bias".