pretrained weight seems not working correctly

[vstar37]

你好，百度网盘中的FPNnet/snapashot/FPNet-GroupInsert中的FPNet.pth 存在解压错误“RuntimeError: PytorchStreamReader failed reading zip archive: failed finding central directory”

能重新上传一下吗？我不知道为为什么我这边3070ti自己训练速度特别慢。

2024-03-21 10:07:37.695567 Epoch [009/300], Step [0480/1010], Total_loss: 2.9832 Loss1: 1.9883 Loss2: 0.9949
2024-03-21 10:09:43.435319 Epoch [009/300], Step [0500/1010], Total_loss: 3.6432 Loss1: 2.4369 Loss2: 1.2063

[RainGameon]

The link to FPNet.pth has been updated to: https://pan.baidu.com/s/1mWV-8dKpmmZFFbafyeTe3w?pwd=qv6n

[KwunYat]

The link to FPNet.pth has been updated to: https://pan.baidu.com/s/1mWV-8dKpmmZFFbafyeTe3w?pwd=qv6n
您好，您给的新的权重链接还是不能用，爆出RuntimeError: Error(s) in loading state_dict for FPNet:
Missing key(s) in state_dict: "FPM1.tram.conv1.conv.weight", "FPM1.tram.conv1.bn.weight", "FPM1.tram.conv1.bn.bias", "FPM1.tram.conv1.bn.running_mean", "FPM1.tram.conv1.bn.running_var", "FPM1.tram.conv2.conv.weight", "FPM1.tram.conv2.bn.weight", "FPM1.tram.conv2.bn.bias", "FPM1.tram.conv2.bn.running_mean", "FPM1.tram.conv2.bn.running_var", "FPM1.tram.conv3.conv.weight", "FPM1.tram.conv3.bn.weight", "FPM1.tram.conv3.bn.bias", "FPM1.tram.conv3.bn.running_mean", "FPM1.tram.conv3.bn.running_var", "FPM1.tram.conv4.conv.weight", "FPM1.tram.conv4.bn.weight", "FPM1.tram.conv4.bn.bias", "FPM1.tram.conv4.bn.running_mean", "FPM1.tram.conv4.bn.running_var", "FPM2.tram.conv1.conv.weight", "FPM2.tram.conv1.bn.weight", "FPM2.tram.conv1.bn.bias", "FPM2.tram.conv1.bn.running_mean", "FPM2.tram.conv1.bn.running_var", "FPM2.tram.conv2.conv.weight", "FPM2.tram.conv2.bn.weight", "FPM2.tram.conv2.bn.bias", "FPM2.tram.conv2.bn.running_mean", "FPM2.tram.conv2.bn.running_var", "FPM2.tram.conv3.conv.weight", "FPM2.tram.conv3.bn.weight", "FPM2.tram.conv3.bn.bias", "FPM2.tram.conv3.bn.running_mean", "FPM2.tram.conv3.bn.running_var", "FPM2.tram.conv4.conv.weight", "FPM2.tram.conv4.bn.weight", "FPM2.tram.conv4.bn.bias", "FPM2.tram.conv4.bn.running_mean", "FPM2.tram.conv4.bn.running_var".
Unexpected key(s) in state_dict: "CFM1.tram.conv1.conv.weight", "CFM1.tram.conv1.bn.weight", "CFM1.tram.conv1.bn.bias", "CFM1.tram.conv1.bn.running_mean", "CFM1.tram.conv1.bn.running_var", "CFM1.tram.conv1.bn.num_batches_tracked", "CFM1.tram.conv2.conv.weight", "CFM1.tram.conv2.bn.weight", "CFM1.tram.conv2.bn.bias", "CFM1.tram.conv2.bn.running_mean", "CFM1.tram.conv2.bn.running_var", "CFM1.tram.conv2.bn.num_batches_tracked", "CFM1.tram.conv3.conv.weight", "CFM1.tram.conv3.bn.weight", "CFM1.tram.conv3.bn.bias", "CFM1.tram.conv3.bn.running_mean", "CFM1.tram.conv3.bn.running_var", "CFM1.tram.conv3.bn.num_batches_tracked", "CFM1.tram.conv4.conv.weight", "CFM1.tram.conv4.bn.weight", "CFM1.tram.conv4.bn.bias", "CFM1.tram.conv4.bn.running_mean", "CFM1.tram.conv4.bn.running_var", "CFM1.tram.conv4.bn.num_batches_tracked", "CFM2.tram.conv1.conv.weight", "CFM2.tram.conv1.bn.weight", "CFM2.tram.conv1.bn.bias", "CFM2.tram.conv1.bn.running_mean", "CFM2.tram.conv1.bn.running_var", "CFM2.tram.conv1.bn.num_batches_tracked", "CFM2.tram.conv2.conv.weight", "CFM2.tram.conv2.bn.weight", "CFM2.tram.conv2.bn.bias", "CFM2.tram.conv2.bn.running_mean", "CFM2.tram.conv2.bn.running_var", "CFM2.tram.conv2.bn.num_batches_tracked", "CFM2.tram.conv3.conv.weight", "CFM2.tram.conv3.bn.weight", "CFM2.tram.conv3.bn.bias", "CFM2.tram.conv3.bn.running_mean", "CFM2.tram.conv3.bn.running_var", "CFM2.tram.conv3.bn.num_batches_tracked", "CFM2.tram.conv4.conv.weight", "CFM2.tram.conv4.bn.weight", "CFM2.tram.conv4.bn.bias", "CFM2.tram.conv4.bn.running_mean", "CFM2.tram.conv4.bn.running_var", "CFM2.tram.conv4.bn.num_batches_tracked".能重新上传一下吗？