コード例 #1
0
ファイル: train_last.py プロジェクト: rcoor/cubed-sphere
if __name__ == '__main__':
    from train import standard_arg_paser, generate_train_cmd, run_cmds, defaults, all_models, all_output_types

    parser = standard_arg_paser()
    args = parser.parse_args()

    # Settings
    checkpoint_base_dir = "/scratch1/rwt891/data/deepfold/camara"
    test_base_dir = "/scratch1/rwt891/data/deepfold/camara_test"

    id_number = "01"

    # Generate commands
    cmds = []

    data_dir_base = "/scratch1/rwt891/data/cull_pdb_pc100_entries_170602/culled_pc30_res3.0_R0.3_d170611/"
    data_name = "pc30"
    num_passes = "10"

    for model in [
            "CubedSphereModel", "SphericalModel", "CartesianHighresModel"
    ]:
        for output_type in all_output_types:

            cmd = generate_train_cmd(
                args.mode,
                model,
                output_type,
                data_name,
                defaults['regularization'],
                defaults['learning_rate'],
コード例 #2
0
ファイル: ddg.py プロジェクト: rcoor/cubed-sphere
        '--model', model
    ]

    if restore_checkpoint == 'best':
        best = get_best_checkpoint(checkpoint_base_dir + "/" + name + ".txt")
        cmd += ["--step", best]

    output_file = output_dir + '/' + ddg_name + '_' + restore_checkpoint + "_" + name + '.txt'

    return cmd, output_file, name


if __name__ == '__main__':
    from train import standard_arg_paser, run_cmds, defaults, all_models, all_output_types

    parser = standard_arg_paser(exclude=['mode'])
    args = parser.parse_args()

    # Settings
    checkpoint_base_dir = "/scratch1/rwt891/data/deepfold/camara"
    output_dir = "/scratch1/rwt891/data/deepfold/camara_ddg"

    ddg_data_dir_base = "/scratch1/rwt891/data/ddgs"

    train_data_name = "pc30"
    train_num_passes = "10"
    train_id_number = "01"

    output_type = 'aa'

    # Generate commands