da_setting adda seems no effect

[xiaoyuan1996]

python train_DA.py -d digits --source svhn --target mnist --da_setting adda

Training target model...
Train Epoch: 22, Batch:937, S: [c: 0.000, d: 1.354], Time: 12.886
Testing target model on [source]...
Test, loss: 4.267, prec: 6.4%, Time: 2.465
Testing target model on [target]...
Test, loss: 4.293, prec: 9.8%, Time: 1.192
73%|████████████████████████████████████████████████████████████████████████████████████▎ | 22/30 [06:11<02:15, 16.93s/it]Training target model...
Train Epoch: 23, Batch:937, S: [c: 0.000, d: 1.429], Time: 12.536
Testing target model on [source]...
Test, loss: 6.942, prec: 7.8%, Time: 2.410
Testing target model on [target]...
Test, loss: 7.577, prec: 10.3%, Time: 1.235
77%|████████████████████████████████████████████████████████████████████████████████████████▏ | 23/30 [06:27<01:57, 16.75s/it]Training target model...
Train Epoch: 24, Batch:937, S: [c: 0.000, d: 1.375], Time: 13.038
Testing target model on [source]...
Test, loss: 14.831, prec: 9.7%, Time: 2.508
Testing target model on [target]...
Test, loss: 15.324, prec: 9.8%, Time: 1.543
80%|████████████████████████████████████████████████████████████████████████████████████████████ | 24/30 [06:44<01:41, 16.91s/it]Training target model...
Train Epoch: 25, Batch:937, S: [c: 0.000, d: 1.367], Time: 12.633
Testing target model on [source]...
Test, loss: 6.635, prec: 6.1%, Time: 2.474
Testing target model on [target]...
Test, loss: 7.577, prec: 10.1%, Time: 1.280
83%|███████████████████████████████████████████████████████████████████████████████████████████████▊ | 25/30 [07:01<01:23, 16.80s/it]Training target model...
Train Epoch: 26, Batch:937, S: [c: 0.000, d: 1.390], Time: 12.824
Testing target model on [source]...
Test, loss: 9.628, prec: 15.9%, Time: 2.390
Testing target model on [target]...
Test, loss: 10.641, prec: 10.3%, Time: 1.202
87%|███████████████████████████████████████████████████████████████████████████████████████████████████▋ | 26/30 [07:17<01:06, 16.73s/it]Training target model...
Train Epoch: 27, Batch:937, S: [c: 0.000, d: 1.447], Time: 12.648
Testing target model on [source]...
Test, loss: 8.766, prec: 11.1%, Time: 3.055
Testing target model on [target]...
Test, loss: 8.690, prec: 10.1%, Time: 1.376

.. bad effect, any problems?

[hou-yz]

Hi,

Thank you for your interest. However, we have no official support for digits datasets using ADDA. The current discriminator architecture in ADDA is designed for stronger classifiers like ResNet50 in VisDA datasets. Directly applying such a strong discriminator might introduce difficulties to the 3-layerl-convolution-classifier in digits datasets in terms of adversarial training.

Feel free to adjust the discriminator architecture a little bit (probably remove a few layers or see other ADDA implementations) to facilitate the digits datasets.

Yunzhong