pytorch-adda
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A PyTorch implementation for Adversarial Discriminative Domain Adaptation
Minimal Code Changes to Support Latest PyTorch and Bug Fixed for Extremely Low Adaptation Accuracy
Thanks for contributing this repo, which is really nice to learn domain adaptation. 1. Just made some minimal code changes to support latest PyTorch (>= 1.0) and Python (>= 3.6)...
=== Evaluating classifier for encoded target domain === >>> only source > source and target
Thanks for sharing the code. I have a question about the line 25 in adapt.py (criterion = nn.CrossEntropyLoss() ). Since nn.LogSoftmax() is added in discriminator.py (line 21). Is it correct...
Downgrading to (py)torch==0.3.1 (required re-processing data) fixed issue. This issue is mainly to help other people who run into the same problem. Here are my results with torch 0.3.1 and...
ERROR!!!
RuntimeError: The expanded size of the tensor (1) must match the existing size (3) at non-singleton dimension 0
The url "https://raw.githubusercontent.com/mingyuliutw/CoGAN/master/cogan_pytorch/data/uspssample/usps_28x28.pkl" for the USPS dataset is fail, how can I reach the newest address. Thanks!
1 I use RNN network as encoder, save the trained model in the source domain and test the USPS data set. The accuracy rate is only 10%, which is not...
Thanks for the code. I changed the dataset. But the adaptation process didn't converge( acc=0.5 represents convergence?), and just get 14% domain adaptation accrucy. Epoch [457/600] Step [100/200]:d_loss=0.32023 g_loss=3.27941 acc=0.89000...
 My d_loss is 0,and my accuracy is 1 .