训练第三步的时候加载模型出现错误 #21
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第二步类似，但是没有缺失。 |
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问题解决了，在训练CycleGan的时候netG_B 是resnet_9blocks ，而在SDehazing中，作者使用预训练模型初始化的时候传递的参数是which_model_netG_A，也就是resnet_9blocks_depth，两个模型不一致会出现缺少键值。 |
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+1 碰到了同样的问题 |
你在训练CycleGAN的时候遇到G_A的loss收敛不了的情况嘛 |
我两个G都是损失忽上忽下，而且一开始的几轮是损失最小的，后面反而变大了 |
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我训练出来是这样的，这种情况正常嘛？
junkai.fan@njust.edu.cn
发件人： Jason Zhang
发送时间： 2021-03-09 21:10
收件人： HUSTSYJ/DA_dahazing
抄送： 樊俊凯; Comment
主题： Re: [HUSTSYJ/DA_dahazing] 训练第三步的时候加载模型出现错误 (#21)
netG_B
你在训练CycleGAN的时候遇到G_A的loss收敛不了的情况嘛
我两个G都是损失忽上忽下，而且一开始的几轮是损失最小的，后面反而变大了
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不知道，我想做去雨的，结果域偏移过程中图像损失太多细节了，糊得一塌糊涂。。现在疯狂调参，可能数据集还要改 |
关于损失函数的变动你可以看看这篇文章，gan的损失和图像质量关系可能不大。 |
按照论文中的结构描述，是要这样改。论文中从R到S是没有用到深度信息的，训练SDehazing时，初始化应该用which_model_netG_B，forward也要改，这样才和论文中一样。就是不知道作者最后的结果，是按照论文中描述训练的，还是按代码训练的。你这样修改后能复现论文中的结果吗？ |
请问你训练是正常的吗，为什么我训练显示 |
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RuntimeError: Error(s) in loading state_dict for ResnetGenerator_depth:
Missing key(s) in state_dict: "modelfea.1.weight", "modelfea.2.weight", "modelfea.2.bias", "modelfea.2.running_mean", "modelfea.2.running_var", "modelfea.4.weight", "modelfea.5.weight", "modelfea.5.bias", "modelfea.5.running_mean", "modelfea.5.running_var", "modelfea.7.weight", "modelfea.8.weight", "modelfea.8.bias", "modelfea.8.running_mean", "modelfea.8.running_var", "modelfea.10.conv_block.1.weight", "modelfea.10.conv_block.2.weight", "modelfea.10.conv_block.2.bias", "modelfea.10.conv_block.2.running_mean", "modelfea.10.conv_block.2.running_var", "modelfea.10.conv_block.5.weight", "modelfea.10.conv_block.6.weight", "modelfea.10.conv_block.6.bias", "modelfea.10.conv_block.6.running_mean", "modelfea.10.conv_block.6.running_var", "modelfea.11.conv_block.1.weight", "modelfea.11.conv_block.2.weight", "modelfea.11.conv_block.2.bias", "modelfea.11.conv_block.2.running_mean", "modelfea.11.conv_block.2.running_var", "modelfea.11.conv_block.5.weight", "modelfea.11.conv_block.6.weight", "modelfea.11.conv_block.6.bias", "modelfea.11.conv_block.6.running_mean", "modelfea.11.conv_block.6.running_var", "modelfea.12.conv_block.1.weight", "modelfea.12.conv_block.2.weight", "modelfea.12.conv_block.2.bias", "modelfea.12.conv_block.2.running_mean", "modelfea.12.conv_block.2.running_var", "modelfea.12.conv_block.5.weight", "modelfea.12.conv_block.6.weight", "modelfea.12.conv_block.6.bias", "modelfea.12.conv_block.6.running_mean", "modelfea.12.conv_block.6.running_var", "modelfea.13.conv_block.1.weight", "modelfea.13.conv_block.2.weight", "modelfea.13.conv_block.2.bias", "modelfea.13.conv_block.2.running_mean", "modelfea.13.conv_block.2.running_var", "modelfea.13.conv_block.5.weight", "modelfea.13.conv_block.6.weight", "modelfea.13.conv_block.6.bias", "modelfea.13.conv_block.6.running_mean", "modelfea.13.conv_block.6.running_var", "modelfea.14.conv_block.1.weight", "modelfea.14.conv_block.2.weight", "modelfea.14.conv_block.2.bias", "modelfea.14.conv_block.2.running_mean", "modelfea.14.conv_block.2.running_var", "modelfea.14.conv_block.5.weight", "modelfea.14.conv_block.6.weight", "modelfea.14.conv_block.6.bias", "modelfea.14.conv_block.6.running_mean", "modelfea.14.conv_block.6.running_var", "modelfea.15.conv_block.1.weight", "modelfea.15.conv_block.2.weight", "modelfea.15.conv_block.2.bias", "modelfea.15.conv_block.2.running_mean", "modelfea.15.conv_block.2.running_var", "modelfea.15.conv_block.5.weight", "modelfea.15.conv_block.6.weight", "modelfea.15.conv_block.6.bias", "modelfea.15.conv_block.6.running_mean", "modelfea.15.conv_block.6.running_var", "modelfea.16.conv_block.1.weight", "modelfea.16.conv_block.2.weight", "modelfea.16.conv_block.2.bias", "modelfea.16.conv_block.2.running_mean", "modelfea.16.conv_block.2.running_var", "modelfea.16.conv_block.5.weight", "modelfea.16.conv_block.6.weight", "modelfea.16.conv_block.6.bias", "modelfea.16.conv_block.6.running_mean", "modelfea.16.conv_block.6.running_var", "modelfea.17.conv_block.1.weight", "modelfea.17.conv_block.2.weight", "modelfea.17.conv_block.2.bias", "modelfea.17.conv_block.2.running_mean", "modelfea.17.conv_block.2.running_var", "modelfea.17.conv_block.5.weight", "modelfea.17.conv_block.6.weight", "modelfea.17.conv_block.6.bias", "modelfea.17.conv_block.6.running_mean", "modelfea.17.conv_block.6.running_var", "modelfea.18.conv_block.1.weight", "modelfea.18.conv_block.2.weight", "modelfea.18.conv_block.2.bias", "modelfea.18.conv_block.2.running_mean", "modelfea.18.conv_block.2.running_var", "modelfea.18.conv_block.5.weight", "modelfea.18.conv_block.6.weight", "modelfea.18.conv_block.6.bias", "modelfea.18.conv_block.6.running_mean", "modelfea.18.conv_block.6.running_var", "modelfea.19.weight", "modelfea.20.weight", "modelfea.20.bias", "modelfea.20.running_mean", "modelfea.20.running_var", "modelfea.22.weight", "modelfea.23.weight", "modelfea.23.bias", "modelfea.23.running_mean", "modelfea.23.running_var", "SFT.condition_conv.0.weight", "SFT.condition_conv.0.bias", "SFT.condition_conv.2.weight", "SFT.condition_conv.2.bias", "SFT.condition_conv.4.weight", "SFT.condition_conv.4.bias", "SFT.scale_conv.0.weight", "SFT.scale_conv.0.bias", "SFT.scale_conv.2.weight", "SFT.scale_conv.2.bias", "SFT.sift_conv.0.weight", "SFT.sift_conv.0.bias", "SFT.sift_conv.2.weight", "SFT.sift_conv.2.bias", "model2.1.weight", "model2.1.bias".
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