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adda-pytorch's Introduction

adda-pytorch

Implementation of "Adversarial Discriminative Domain Adaptation"(https://arxiv.org/abs/1702.05464) on pytorch

dataset

mnist -> usps
usps -> mnist

command

$ python train_src.py --config "A->B config-file"

#training a model on source domain data
"A->B config-file" should be usps2mnist.yaml or mnist2usps.yaml
val reports the accuracy on target data

$ python main.py --config "A->B config-file"

#adapt the model trained on source data to fit target data with ADDA method
"A->B config-file" should be usps2mnist.yaml or mnist2usps.yaml

performance on testing set

Method mnist -> usps usps -> mnist
source only 84% (1560/1860) 78% (7820/10000)
adapted 92% (1709/1860) 91% (9074/10000)

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adda-pytorch's Issues

Losses

In ADDA, classifier loss and advarsarial loss are used. In which file you are using these two losses ?

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