segmentation/tool/train.py [24:61]:
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cv2.ocl.setUseOpenCL(False)
cv2.setNumThreads(0)


def get_parser():
    parser = argparse.ArgumentParser(description='PyTorch Semantic Segmentation')
    parser.add_argument('--config', type=str, default='config/ade20k/ade20k_pspnet50.yaml', help='config file')
    parser.add_argument('opts', help='see config/ade20k/ade20k_pspnet50.yaml for all options', default=None, nargs=argparse.REMAINDER)
    args = parser.parse_args()
    assert args.config is not None
    cfg = config.load_cfg_from_cfg_file(args.config)
    if args.opts is not None:
        cfg = config.merge_cfg_from_list(cfg, args.opts)
    return cfg


def get_logger():
    logger_name = "main-logger"
    logger = logging.getLogger(logger_name)
    logger.setLevel(logging.INFO)
    handler = logging.StreamHandler()
    fmt = "[%(asctime)s %(levelname)s %(filename)s line %(lineno)d %(process)d] %(message)s"
    handler.setFormatter(logging.Formatter(fmt))
    logger.addHandler(handler)
    return logger


def worker_init_fn(worker_id):
    random.seed(args.manual_seed + worker_id)


def main_process():
    return not args.multiprocessing_distributed or (args.multiprocessing_distributed and args.rank % args.ngpus_per_node == 0)


def check(args):
    assert args.classes > 1
    assert args.zoom_factor in [1, 2, 4, 8]
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segmentation/tool/train_cnsn.py [24:61]:
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cv2.ocl.setUseOpenCL(False)
cv2.setNumThreads(0)


def get_parser():
    parser = argparse.ArgumentParser(description='PyTorch Semantic Segmentation')
    parser.add_argument('--config', type=str, default='config/ade20k/ade20k_pspnet50.yaml', help='config file')
    parser.add_argument('opts', help='see config/ade20k/ade20k_pspnet50.yaml for all options', default=None, nargs=argparse.REMAINDER)
    args = parser.parse_args()
    assert args.config is not None
    cfg = config.load_cfg_from_cfg_file(args.config)
    if args.opts is not None:
        cfg = config.merge_cfg_from_list(cfg, args.opts)
    return cfg


def get_logger():
    logger_name = "main-logger"
    logger = logging.getLogger(logger_name)
    logger.setLevel(logging.INFO)
    handler = logging.StreamHandler()
    fmt = "[%(asctime)s %(levelname)s %(filename)s line %(lineno)d %(process)d] %(message)s"
    handler.setFormatter(logging.Formatter(fmt))
    logger.addHandler(handler)
    return logger


def worker_init_fn(worker_id):
    random.seed(args.manual_seed + worker_id)


def main_process():
    return not args.multiprocessing_distributed or (args.multiprocessing_distributed and args.rank % args.ngpus_per_node == 0)


def check(args):
    assert args.classes > 1
    assert args.zoom_factor in [1, 2, 4, 8]
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