columnformers/topomoe/tests/test_train.py at 79549b16e3202f4e0d462db1480c599eebc801bb · clane9/columnformers · GitHub

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import pytest
from topomoe import train

configs = {
    "vit_small": train.Args(
        name="debug_train_vit_small",
        out_dir="topomoe/test_results",
        model="vit_small_patch16_224",
        dataset="hfds/clane9/imagenet-100",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "vit_base": train.Args(
        name="debug_train_vit_base",
        out_dir="topomoe/test_results",
        model="vit_base_patch16_224",
        dataset="hfds/clane9/imagenet-100",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "transformer": train.Args(
        name="debug_train_transformer",
        out_dir="topomoe/test_results",
        model="quadmoe_tiny_1s_patch16_128",
        dataset="hfds/clane9/imagenet-100",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "transformer_v2": train.Args(
        name="debug_train_transformer_v2",
        out_dir="topomoe/test_results",
        model="topomoe_tiny_1s_patch16_128",
        dataset="hfds/clane9/imagenet-100",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "quadmoe": train.Args(
        name="debug_train_quadmoe",
        out_dir="topomoe/test_results",
        model="quadmoe_tiny_2s_patch16_128",
        dataset="hfds/clane9/imagenet-100",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "softmoe": train.Args(
        name="debug_train_softmoe",
        out_dir="topomoe/test_results",
        model="softmoe_tiny_2s_patch16_128",
        dataset="hfds/clane9/imagenet-100",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "topomoe": train.Args(
        name="debug_train_topomoe",
        data_dir="/weka/proj-medarc/shared/imagenet",
        out_dir="topomoe/test_results",
        model="topomoe_tiny_2s_patch16_128",
        wiring_lambd=0.01,
        dataset="folder",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "aug": train.Args(
        name="debug_train_aug",
        out_dir="topomoe/test_results",
        model="quadmoe_tiny_1s_patch16_128",
        dataset="hfds/clane9/imagenet-100",
        scale=[0.1, 0.3],
        ratio=[1 / 4, 4 / 1],
        hflip=0.5,
        color_jitter=0.4,
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
    "topomoe_small": train.Args(
        name="debug_train_topomoe_small",
        out_dir="topomoe/test_results",
        model="topomoe_small_2s_patch16_224",
        wiring_lambd=0.01,
        dataset="hfds/clane9/imagenet-100",
        workers=0,
        batch_size=32,
        overwrite=True,
        debug=True,
    ),
}


@pytest.mark.parametrize(
    "config",
    [
        "vit_small",
        "vit_base",
        "transformer",
        "transformer_v2",
        "quadmoe",
        "softmoe",
        "topomoe",
        "aug",
        "topomoe_small",
    ],
)
def test_train(config: str):
    args = configs[config]
    train.main(args)


if __name__ == "__main__":
    import argparse

    parser = argparse.ArgumentParser(description="Run training configurations.")
    parser.add_argument(
        "--config",
        nargs="+",
        default=None,
        help="List of configurations to run. If not specified, all configurations will be run.",
    )

    parsed_args = parser.parse_args()

    if parsed_args.config is not None:
        configs_to_run = parsed_args.config
    else:
        configs_to_run = configs.keys()

    for config in configs_to_run:
        if config in configs:
            print(f"Running configuration: {config}")
            test_train(config)
        else:
            print(f"Configuration '{config}' not found.")