add_job(
            job_type, 2, "ResNet50", "imageNetCaffe2",
            "models/imagenet-caffe-resnet50-features-ac468af-converted.pth")
        add_job(job_type, 3, "ResNet50", "imageNetCaffe2GroupNorm",
                "models/resnet50_caffe2_groupnorm.pth",
                {"model.use_group_norm": True})
        add_job(
            job_type, 4, "ResNet50", "cocoMaskrcnnFpn",
            "models/maskrcnn-benchmark/e2e_mask_rcnn_R_50_FPN_1x_converted.pth"
        )
        add_job(job_type, 5, "ResNet101", "imageNetPth",
                "models/resnet101-5d3b4d8f.pth")
        add_job(
            job_type, 6, "ResNet101", "imageNetCaffe2",
            "models/imagenet-caffe-resnet101-features-10a101d-converted.pth")
        add_job(job_type, 7, "ResNet101", "buildingsCirtorch",
                "models/gl18-tl-resnet101-gem-w-a4d43db-converted.pth")
        add_job(
            job_type, 8, "ResNet101", "cocoMaskrcnnFpn",
            "models/maskrcnn-benchmark/e2e_mask_rcnn_R_101_FPN_1x_converted.pth"
        )
        add_job(job_type, 9, "ResNet101", "pascalWeakalign",
                "models/weakalign_resnet101_affine_tps.pth.tar")

    for job_name, log_path, commands in zip(exp_job_names, exp_log_paths,
                                            exp_commands):
        launcher.add_job(job_name=job_name,
                         log_path=log_path,
                         commands=commands)
    launcher.launch_all_jobs(args)
            eval_dataset,
            "output/exp1/exp1.8.lossRLL_remap_invFullAffine_initTranform_zeroLocLoss_mine_seed0_ResNet50_init_imageNetCaffe2",
            model_checkpoint=
            "*****@*****.**",
            folder_suffix="best_V2-train")
        # Best v2 init model
        add_job(
            2,
            "v2",
            "ResNet50",
            eval_dataset,
            "output/exp1/exp1.8.lossRLL_remap_invFullAffine_initTranform_zeroLocLoss_mine_seed0_ResNet50_init_imageNetCaffe2",
            model_checkpoint="checkpoint_iter_0.pth",
            folder_suffix="best_V2-init")
        # Sliding window baseline (identity transformation model)
        add_job(3,
                "v1",
                "ResNet101",
                eval_dataset,
                "output/exp2/exp2.7.v1_seed0_ResNet101_init_buildingsCirtorch",
                model_checkpoint="checkpoint_iter_0.pth",
                folder_suffix="best_V1-init")

    for job_name, log_path, commands, log_file_prefix in zip(
            exp_job_names, exp_log_paths, exp_commands, exp_log_file_prefix):
        launcher.add_job(job_name=job_name,
                         log_path=log_path,
                         commands=commands,
                         log_file_prefix=log_file_prefix)
    launcher.launch_all_jobs(args)