python train_model.py \
        name=imagenet_c \
        problem=imagenet_c \
        problem/model=dt_net_2d_custom \
        problem.model.model=imagenet_gru \
        problem.model.num_class=1000 \
        problem.model.width=1024 \
        problem.train_data_path="/home/fis/workspace_AI/AI-RnD/hieutb2/DATA/train" \
        problem.test_data_path="/home/fis/workspace_AI/AI-RnD/hieutb2/DATA/val" \
        problem.model.max_iters=10 \
        problem.hyp.epochs=50 \
        problem.hyp.alpha=0.0 \
        problem.hyp.beta=0.5 \
        problem.hyp.act=0.0 \
        problem.hyp.train_batch_size=2 \
        problem.hyp.noise_problem='Gaussian Noise' \

