Random Search Algorithm¶
Random sampler as optimization algorithm¶
Draw and deliver samples from prior defined in problem’s domain.
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class
orion.algo.random.
Random
(space, seed=None)[source]¶ Implement a algorithm that samples randomly from the problem’s space.
Attributes: state_dict
Return a state dict that can be used to reset the state of the algorithm.
Methods
seed_rng
(seed)Seed the state of the random number generator. set_state
(state_dict)Reset the state of the algorithm based on the given state_dict suggest
([num])Suggest a num of new sets of parameters. -
seed_rng
(seed)[source]¶ Seed the state of the random number generator.
Parameters: seed – Integer seed for the random number generator.
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set_state
(state_dict)[source]¶ Reset the state of the algorithm based on the given state_dict
Parameters: state_dict – Dictionary representing state of an algorithm
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state_dict
¶ Return a state dict that can be used to reset the state of the algorithm.
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suggest
(num=1)[source]¶ Suggest a num of new sets of parameters. Randomly draw samples from the import space and return them.
Parameters: num – how many sets to be suggested. Note
New parameters must be compliant with the problem’s domain
orion.algo.space.Space
.