Comments (2)
thx for the reply
I see, so what I did is correct, firstly I trained the Enet model and obtained the trained Enet model(pt), then I replace the G_ckpt in train.json with the trained Enet model(pt) and train the Tnet model.
I also agree with you that we should not run the two trainers at the same time.
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Basically after training Enet, you should create a new training config json file and point the Enet checkpoint:
https://github.com/cvlab-stonybrook/PaperEdge/blob/main/configs/train.json#L7
https://github.com/cvlab-stonybrook/PaperEdge/blob/main/train.py#L50-L51
then in train_L_step_w
the Enet is running with the weights from the previous step.
(sry there are some name confusion for Enet, Gnet, Tnet, Lnet...train and eval have different names...)
train_L_step_w
is enough. Do not use 2 engines at the same time...(at least I have not tried)
(sry it took me longer and longer to read all the emails...)
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Related Issues (17)
- Where can I find paper? HOT 1
- Question about joint training HOT 1
- hello, I have a question about AD metric HOT 2
- could you please tell us something about the training? HOT 3
- Why should we train NetL separately in train_L_step_w HOT 1
- Background data problem HOT 7
- Question about train.py HOT 2
- Questions about the source of the dataset in bgtex.txt
- Enet and Tnet trained only on the Doc3D dataset
- where to download bgtex data? HOT 2
- 您好,能问一下文档bgtex.txt中的图片对应的是什么数据集吗?
- Question about training Tnet model only using real data HOT 19
- could you please offer more info for rookies like me to run the code? HOT 5
- Question about train list in the code HOT 6
- A miss module in code HOT 2
- doc3d dataset 403 forbidden HOT 2
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