cotengra.hyperoptimizers.hyper_random

Fake hyper optimization using random sampling.

Module Contents

Classes

RandomSpace
RandomSampler

Functions

sample_bool()
sample_int(low, high)
sample_option(options)
sample_uniform(low, high)
sample_loguniform(low, high)
random_init_optimizers(self, methods, space)	Initialize a completely random sampling optimizer.
random_get_setting(self)
random_report_result(*_, **__)

cotengra.hyperoptimizers.hyper_random.sample_bool()

cotengra.hyperoptimizers.hyper_random.sample_int(low, high)

cotengra.hyperoptimizers.hyper_random.sample_option(options)

cotengra.hyperoptimizers.hyper_random.sample_uniform(low, high)

cotengra.hyperoptimizers.hyper_random.sample_loguniform(low, high)

class cotengra.hyperoptimizers.hyper_random.RandomSpace(space)

sample()

class cotengra.hyperoptimizers.hyper_random.RandomSampler(methods, spaces)

ask()

cotengra.hyperoptimizers.hyper_random.random_init_optimizers(self, methods, space)

Initialize a completely random sampling optimizer.

Parameters:

space (dict[str, dict[str, dict]]) – The search space.

cotengra.hyperoptimizers.hyper_random.random_get_setting(self)

cotengra.hyperoptimizers.hyper_random.random_report_result(*_, **__)