scripts/ablation/tim_gd/weighting_effect.sh
# # ================> mini-Imagenet <=================
# # ========================================
# Only Xent
python3 -m src.main \
        -F logs/ablation/tim_gd/mini \
        with dataset.path="data/mini_imagenet" \
        ckpt_path="checkpoints/mini/softmax/resnet18" \
        dataset.split_dir="split/mini" \
        model.arch='resnet18' \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 0., 0.]" \


# No H(Y)
python3 -m src.main \
        -F logs/ablation/tim_gd/mini \
        with dataset.path="data/mini_imagenet" \
        ckpt_path="checkpoints/mini/softmax/resnet18" \
        dataset.split_dir="split/mini" \
        model.arch='resnet18' \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 0., 0.1]" \


# No H(Y|X)
python3 -m src.main \
        -F logs/ablation/tim_gd/mini \
        with dataset.path="data/mini_imagenet" \
        ckpt_path="checkpoints/mini/softmax/resnet18" \
        dataset.split_dir="split/mini" \
        model.arch='resnet18' \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 1.0, 0.]" \

# Full loss
python3 -m src.main \
        -F logs/ablation/tim_gd/mini \
        with dataset.path="data/mini_imagenet" \
        ckpt_path="checkpoints/mini/softmax/resnet18" \
        dataset.split_dir="split/mini" \
        model.arch='resnet18' \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 1.0, 0.1]" \


# # ================> tiered-Imagenet <=================
# # ========================================

# Only XEnt
python3 -m src.main \
        -F logs/ablation/tim_gd/tiered \
        with dataset.path="data/tiered_imagenet/data" \
        ckpt_path="checkpoints/tiered/softmax/resnet18" \
        dataset.split_dir="split/tiered" \
        model.arch='resnet18' \
        model.num_classes=351 \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 0., 0.]" \


# No H(Y)
python3 -m src.main \
        -F logs/ablation/tim_gd/tiered \
        with dataset.path="data/tiered_imagenet/data" \
        ckpt_path="checkpoints/tiered/softmax/resnet18" \
        dataset.split_dir="split/tiered" \
        model.arch='resnet18' \
        model.num_classes=351 \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 0., 0.1]" \

# No H(Y|X)
python3 -m src.main \
        -F logs/ablation/tim_gd/tiered \
        with dataset.path="data/tiered_imagenet/data" \
        ckpt_path="checkpoints/tiered/softmax/resnet18" \
        dataset.split_dir="split/tiered" \
        model.num_classes=351 \
        model.arch='resnet18' \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 1.0, 0.]" \

# No H(Y|X)
python3 -m src.main \
        -F logs/ablation/tim_gd/tiered \
        with dataset.path="data/tiered_imagenet/data" \
        ckpt_path="checkpoints/tiered/softmax/resnet18" \
        dataset.split_dir="split/tiered" \
        model.num_classes=351 \
        model.arch='resnet18' \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 1.0, 0.1]" \


# ================> CUB <=================
# ========================================

# Only XEnt
python3 -m src.main \
        -F logs/ablation/tim_gd/cub \
        with dataset.path="data/cub/CUB_200_2011/images" \
        ckpt_path="checkpoints/cub/softmax/resnet18" \
        dataset.split_dir="split/cub" \
        model.arch='resnet18' \
        model.num_classes=100 \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 0., 0.]" \


# No H(Y)
python3 -m src.main \
        -F logs/ablation/tim_gd/cub \
        with dataset.path="data/cub/CUB_200_2011/images" \
        ckpt_path="checkpoints/cub/softmax/resnet18" \
        dataset.split_dir="split/cub" \
        model.arch='resnet18' \
        model.num_classes=100 \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 0., 0.1]" \

# No H(Y|X)
python3 -m src.main \
        -F logs/ablation/tim_gd/cub \
        with dataset.path="data/cub/CUB_200_2011/images" \
        ckpt_path="checkpoints/cub/softmax/resnet18" \
        dataset.split_dir="split/cub" \
        model.arch='resnet18' \
        model.num_classes=100 \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 1.0, 0.]" \

# Full loss
python3 -m src.main \
        -F logs/ablation/tim_gd/cub \
        with dataset.path="data/cub/CUB_200_2011/images" \
        ckpt_path="checkpoints/cub/softmax/resnet18" \
        dataset.split_dir="split/cub" \
        model.arch='resnet18' \
        model.num_classes=100 \
        evaluate=True \
        eval.method='tim_gd' \
        tim.iter=1000 \
        tim.loss_weights="[0.1, 1.0, 0.1]" \