Create a new conda environment and execute setup.sh
.
Alternatively
pip install -r requirements.txt
It is advised to run experiments on a GPU otherwise training might take long.
Use DEVICE cuda
to turn on GPU support, default is cpu
.
Don't forget to specify CUDA_VISIBLE_DEVICES
before python
if you use cuda
nohup python -u run.py DEVICE cuda DATASET jf17k > logs/nohup_shrink_jf17k_200_new.out 2>&1 &
You should obtain the following results after training (see logging file at logs/nohup_shrink_jf17k_200_new.out)
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