Tune Search Space API#

This section covers the functions you can use to define your search spaces.

Caution

Not all Search Algorithms support all distributions. In particular, tune.sample_from and tune.grid_search are often unsupported. The default Random search and grid search (tune.search.basic_variant.BasicVariantGenerator) supports all distributions.

Tip

Avoid passing large objects as values in the search space, as that will incur a performance overhead. Use tune.with_parameters to pass large objects in or load them inside your trainable from disk (making sure that all nodes have access to the files) or cloud storage. See How can I avoid bottlenecks? for more information.

For a high-level overview, see this example:

config = {
    # Sample a float uniformly between -5.0 and -1.0
    "uniform": tune.uniform(-5, -1),

    # Sample a float uniformly between 3.2 and 5.4,
    # rounding to multiples of 0.2
    "quniform": tune.quniform(3.2, 5.4, 0.2),

    # Sample a float uniformly between 0.0001 and 0.01, while
    # sampling in log space
    "loguniform": tune.loguniform(1e-4, 1e-2),

    # Sample a float uniformly between 0.0001 and 0.1, while
    # sampling in log space and rounding to multiples of 0.00005
    "qloguniform": tune.qloguniform(1e-4, 1e-1, 5e-5),

    # Sample a random float from a normal distribution with
    # mean=10 and sd=2
    "randn": tune.randn(10, 2),

    # Sample a random float from a normal distribution with
    # mean=10 and sd=2, rounding to multiples of 0.2
    "qrandn": tune.qrandn(10, 2, 0.2),

    # Sample a integer uniformly between -9 (inclusive) and 15 (exclusive)
    "randint": tune.randint(-9, 15),

    # Sample a random uniformly between -21 (inclusive) and 12 (inclusive (!))
    # rounding to multiples of 3 (includes 12)
    # if q is 1, then randint is called instead with the upper bound exclusive
    "qrandint": tune.qrandint(-21, 12, 3),

    # Sample a integer uniformly between 1 (inclusive) and 10 (exclusive),
    # while sampling in log space
    "lograndint": tune.lograndint(1, 10),

    # Sample a integer uniformly between 1 (inclusive) and 10 (inclusive (!)),
    # while sampling in log space and rounding to multiples of 2
    # if q is 1, then lograndint is called instead with the upper bound exclusive
    "qlograndint": tune.qlograndint(1, 10, 2),

    # Sample an option uniformly from the specified choices
    "choice": tune.choice(["a", "b", "c"]),

    # Sample from a random function, in this case one that
    # depends on another value from the search space
    "func": tune.sample_from(lambda spec: spec.config.uniform * 0.01),

    # Do a grid search over these values. Every value will be sampled
    # ``num_samples`` times (``num_samples`` is the parameter you pass to ``tune.TuneConfig``,
    # which is taken in by ``Tuner``)
    "grid": tune.grid_search([32, 64, 128])
}

Random Distributions API#

`tune.uniform`	Sample a float value uniformly between `lower` and `upper`.
`tune.quniform`	Sample a quantized float value uniformly between `lower` and `upper`.
`tune.loguniform`	Sugar for sampling in different orders of magnitude.
`tune.qloguniform`	Sugar for sampling in different orders of magnitude.
`tune.randn`	Sample a float value normally with `mean` and `sd`.
`tune.qrandn`	Sample a float value normally with `mean` and `sd`.
`tune.randint`	Sample an integer value uniformly between `lower` and `upper`.
`tune.qrandint`	Sample an integer value uniformly between `lower` and `upper`.
`tune.lograndint`	Sample an integer value log-uniformly between `lower` and `upper`.
`tune.qlograndint`	Sample an integer value log-uniformly between `lower` and `upper`.
`tune.choice`	Sample a categorical value.

Grid Search and Custom Function APIs#

`tune.grid_search`	Specify a grid of values to search over.
`tune.sample_from`	Specify that tune should sample configuration values from this function.

Tune Search Space API#

Random Distributions API#

Grid Search and Custom Function APIs#

References#