about the traininig about attentive-gan-derainnet HOT 8 CLOSED

@hezw2016 1.About the init training learning rate it my mistake to write a wrong value in the readme file. The model was trained with the initialized lr 0.002. About the D_loss value problem you may put more details here to discuss it maybe some console print info for example:)
2. When I train my model the data augmentation was not used at all. The reason why I not use it is simply that I do not want to write those code==!. The cropped patches can be used as training images here and the method is quite efficient when I implement another derain task in the paper "Learning Dual Convolutional Neural Networks for Low-Level Vision"(http://faculty.ucmerced.edu/mhyang/papers/cvpr2018_dual_cnn.pdf). If you want to use the cropped patches as training samples you'd better the patches you cropped contain valid rain drop there:)

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@MaybeShewill-CV
Thx for your reply.
I will re-train the model to see whether the problem still exists or not. If so, I will provide some details. : )

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@hezw2016 If you re-train a model with the cropped patches you're welcome to share the result here. It may also help me and other people:)

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@MaybeShewill-CV OK, no problem, it may take several days on my 1070 GPU. HaHa

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@MaybeShewill-CV Hi, the D_loss problem happens again.
At the begining, D_loss is around 15.94, then the D_loss suddenly becomes very large.
here is some details:
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I1112 12:18:20.574566 21056 train_model.py:209] =====>Epoch: 6676 D_loss: 225723.28125 G_loss: 1.69909 Ssim: 0.76703 Cost_time: 1.06179s
I1112 12:18:21.646596 21056 train_model.py:209] =====>Epoch: 6677 D_loss: 120077.87500 G_loss: 1.64597 Ssim: 0.79087 Cost_time: 1.07203s
I1112 12:18:22.716292 21056 train_model.py:209] =====>Epoch: 6678 D_loss: 82806.89844 G_loss: 2.30736 Ssim: 0.72235 Cost_time: 1.06869s
I1112 12:18:23.811926 21056 train_model.py:209] =====>Epoch: 6679 D_loss: 102868.09375 G_loss: 0.90170 Ssim: 0.66528 Cost_time: 1.09463s
I1112 12:18:24.892297 21056 train_model.py:209] =====>Epoch: 6680 D_loss: 118568.27344 G_loss: 2.06072 Ssim: 0.77135 Cost_time: 1.07936s
I1112 12:18:25.973346 21056 train_model.py:209] =====>Epoch: 6681 D_loss: 40991.67969 G_loss: 2.10659 Ssim: 0.71723 Cost_time: 1.08005s
I1112 12:18:27.051629 21056 train_model.py:209] =====>Epoch: 6682 D_loss: 153677.87500 G_loss: 1.27149 Ssim: 0.80044 Cost_time: 1.07728s
I1112 12:18:28.111481 21056 train_model.py:209] =====>Epoch: 6683 D_loss: 119695.32031 G_loss: 2.99901 Ssim: 0.57306 Cost_time: 1.05684s
++++++++++++++++++++++++++++

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I wonder if you can provide the tfevents file?

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@hezw2016 ok I'will check it. The tfevents file will be uploaded later:)

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我也遇到同样的问题，D_loss值很大，能达到十几万，请问这个问题怎么解决？是不是跟log函数的参数有0存在的原因，比如log(0)？

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