Support of log_base for opt_range(type=int)

[vikmary]

Hi!

Thank you for the library! Using it in par with pytorch-lightning to search network's hyperparameters.
Right now the following line:

parser = HyperOptArgumentParser()
parser.opt_range('--batch-size', type=int, default=1500, tunable=True, low=16, high=8192, nb_samples=10, log_base=10)

hparams = parser.parse_args()
for trial_hparams in hparams.trials(10):
    print(vars(trial_hparams))

will produce real values, though

parser = HyperOptArgumentParser()
parser.opt_range('--batch-size', type=int, default=1500, tunable=True, low=16, high=8192, nb_samples=10)

hparams = parser.parse_args()
for trial_hparams in hparams.trials(10):
    print(vars(trial_hparams))

produces int values.

It would be nice to have a feature of sampling in log scale for integer values!