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Support of log_base for opt_range(type=int)
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!