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#
Sample a float value uniformly between |
|
Sample a quantized float value uniformly between |
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Sugar for sampling in different orders of magnitude. |
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Sugar for sampling in different orders of magnitude. |
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Sample a float value normally with |
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Sample a float value normally with |
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Sample an integer value uniformly between |
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Sample an integer value uniformly between |
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Sample an integer value log-uniformly between |
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Sample an integer value log-uniformly between |
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Sample a categorical value. |
Grid Search and Custom Function APIs#
Specify a grid of values to search over. |
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Specify that tune should sample configuration values from this function. |
References#
See also Random search and grid search (tune.search.basic_variant.BasicVariantGenerator).