sample_from#

ray.tune.sample_from(func: Callable[[Dict], Any])[source]#

Specify that tune should sample configuration values from this function.

Use sample_from to define conditional search spaces, where the value sampled for one parameter depends on the value sampled for another. The callable receives the config dict, which exposes the values already sampled for the trial.

Parameters:: func – A callable function to draw a sample from.
Returns:: A Function domain that samples values by calling func.

Example

>>> import numpy as np
>>> from ray import tune
>>> # Sample ``b`` from a range that depends on the value of ``a``.
>>> param_space = {
...     "a": tune.randint(5, 10),
...     "b": tune.sample_from(
...         lambda config: np.random.randint(0, config["a"])
...     ),
... }