python train_model.py \
        name=mnist_c_cnn_ligru \
        problem=mnist_c \
        problem/model=dt_net_2d_custom \
        problem.model.model=cnn_ligru \
        problem.model.num_class=10 \
        problem.hyp.epochs=200 \
        problem.hyp.alpha=0.0 \
        problem.hyp.beta=0.5 \
        problem.hyp.noise_problem='gaussian_noise'

# shot_noise
# impulse_noise
# glass_blur
# motion_blur
# shear
# scale
# rotate
# brightness
# translate
# stripe
# fog
# spatter
# dotted_line
# zigzag
# canny_edges