Search Space API
Contents
Search Space API#
Random Distributions 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.
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])
}
tune.uniform#
tune.quniform#
- ray.tune.quniform(lower: float, upper: float, q: float)[source]#
Sample a quantized float value uniformly between
lower
andupper
.Sampling from
tune.uniform(1, 10)
is equivalent to sampling fromnp.random.uniform(1, 10))
The value will be quantized, i.e. rounded to an integer increment of
q
. Quantization makes the upper bound inclusive.PublicAPI: This API is stable across Ray releases.
tune.loguniform#
- ray.tune.loguniform(lower: float, upper: float, base: float = 10)[source]#
Sugar for sampling in different orders of magnitude.
- Parameters
lower – Lower boundary of the output interval (e.g. 1e-4)
upper – Upper boundary of the output interval (e.g. 1e-2)
base – Base of the log. Defaults to 10.
PublicAPI: This API is stable across Ray releases.
tune.qloguniform#
- ray.tune.qloguniform(lower: float, upper: float, q: float, base: float = 10)[source]#
Sugar for sampling in different orders of magnitude.
The value will be quantized, i.e. rounded to an integer increment of
q
.Quantization makes the upper bound inclusive.
- Parameters
lower – Lower boundary of the output interval (e.g. 1e-4)
upper – Upper boundary of the output interval (e.g. 1e-2)
q – Quantization number. The result will be rounded to an integer increment of this value.
base – Base of the log. Defaults to 10.
PublicAPI: This API is stable across Ray releases.
tune.randn#
tune.qrandn#
- ray.tune.qrandn(mean: float, sd: float, q: float)[source]#
Sample a float value normally with
mean
andsd
.The value will be quantized, i.e. rounded to an integer increment of
q
.- Parameters
mean – Mean of the normal distribution.
sd – SD of the normal distribution.
q – Quantization number. The result will be rounded to an integer increment of this value.
PublicAPI: This API is stable across Ray releases.
tune.randint#
- ray.tune.randint(lower: int, upper: int)[source]#
Sample an integer value uniformly between
lower
andupper
.lower
is inclusive,upper
is exclusive.Sampling from
tune.randint(10)
is equivalent to sampling fromnp.random.randint(10)
Changed in version 1.5.0: When converting Ray Tune configs to searcher-specific search spaces, the lower and upper limits are adjusted to keep compatibility with the bounds stated in the docstring above.
PublicAPI: This API is stable across Ray releases.
tune.qrandint#
- ray.tune.qrandint(lower: int, upper: int, q: int = 1)[source]#
Sample an integer value uniformly between
lower
andupper
.lower
is inclusive,upper
is also inclusive (!).The value will be quantized, i.e. rounded to an integer increment of
q
. Quantization makes the upper bound inclusive.Changed in version 1.5.0: When converting Ray Tune configs to searcher-specific search spaces, the lower and upper limits are adjusted to keep compatibility with the bounds stated in the docstring above.
PublicAPI: This API is stable across Ray releases.
tune.lograndint#
- ray.tune.lograndint(lower: int, upper: int, base: float = 10)[source]#
Sample an integer value log-uniformly between
lower
andupper
, withbase
being the base of logarithm.lower
is inclusive,upper
is exclusive.Changed in version 1.5.0: When converting Ray Tune configs to searcher-specific search spaces, the lower and upper limits are adjusted to keep compatibility with the bounds stated in the docstring above.
PublicAPI: This API is stable across Ray releases.
tune.qlograndint#
- ray.tune.qlograndint(lower: int, upper: int, q: int, base: float = 10)[source]#
Sample an integer value log-uniformly between
lower
andupper
, withbase
being the base of logarithm.lower
is inclusive,upper
is also inclusive (!).The value will be quantized, i.e. rounded to an integer increment of
q
. Quantization makes the upper bound inclusive.Changed in version 1.5.0: When converting Ray Tune configs to searcher-specific search spaces, the lower and upper limits are adjusted to keep compatibility with the bounds stated in the docstring above.
PublicAPI: This API is stable across Ray releases.
tune.choice#
tune.sample_from#
Grid Search API#
References#
See also Random search and grid search (tune.search.basic_variant.BasicVariantGenerator).