def add_arguments(parser) -> None:
    """Function to add common arguments to argparse:
    feature_dim: Feature dim for latent vector
    temperature: Temperature used in softmax
    batch_size: Number of images in each mini-batch
    epochs: Number of sweeps over the dataset to train
    num_workers: Number of workers to process a dataloader
    logdir: Logs directory (tensorboard, weights, etc)
    dataset: CIFAR-10, CIFAR-100 or STL10
    learning-rate: Learning rate for optimizer

    Args:
        parser: argparser like object
    """
    parser.add_argument(
        "--dataset",
        default="CIFAR-10",
        type=str,
        choices=DATASETS.keys(),
        help="Dataset: CIFAR-10, CIFAR-100 or STL10",
    )
    parser.add_argument(
        "--logdir",
        default="./logdir",
        type=str,
        help="Logs directory (tensorboard, weights, etc)",
    )
    parser.add_argument(
        "--epochs",
        default=1000,
        type=int,
        help="Number of sweeps over the dataset to train",
    )
    parser.add_argument(
        "--num-workers",
        default=1,
        type=float,
        help="Number of workers to process a dataloader",
    )
    parser.add_argument(
        "--batch-size", default=512, type=int, help="Number of images in each mini-batch"
    )
    parser.add_argument(
        "--feature-dim", default=128, type=int, help="Feature dim for latent vector"
    )
    parser.add_argument(
        "--temperature", default=0.5, type=float, help="Temperature used in softmax"
    )
    parser.add_argument(
        "--learning-rate", default=0.001, type=float, help="Learning rate for optimizer"
    )
    # boolean_flag(parser=parser, name="check", default=False)
    boolean_flag(parser=parser, name="verbose", default=False)
Function to add common arguments to argparse:
    feature_dim: Feature dim for latent vector
    temperature: Temperature used in softmax
    batch_size: Number of images in each mini-batch
    epochs: Number of sweeps over the dataset to train
    num_workers: Number of workers to process a dataloader
    logdir: Logs directory (tensorboard, weights, etc)
    dataset: CIFAR-10, CIFAR-100 or STL10
    learning-rate: Learning rate for optimizer

    Args:
        parser: argparser like object
    
examples/self_supervised/src/common.py