Domain Adaptation with Invariant RepresentationLearning: What Transformations to Learn?

Repository Structure:

DSAN
|└───amazon
|    └── dataset (Amazon dataset)
|    ├── result
|    ├── amazon_utils.py
|    ├── dsan.py
|    └── flip_gradient.py
|    └── logger.py
|────imageclef
|    └── dataset (ImageCLEF dataset)
|    ├── logs
|    ├── utils.py
|    ├── dsan.py
|    └── flip_gradient.py

Instructions on running the code: ##1. Run the following command

# for Amazon
cd amazon
python dsan.py --src $source_domain_name --tgt $target_domain_name 

# for ImageCLEF
cd imageclef
python dsan.py --src $source_domain_name --tgt $target_domain_name

##2. Compute environment for our experiments:
CPU: Intel 7700k
GPU: GeForce RTX2070
32 GB Memory
##3. Table of the experiment result for Amazon: