Random Search Algorithm¶
Random sampler as optimization algorithm¶
Draw and deliver samples from prior defined in problem’s domain.
-
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.
-
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
-
property
state_dict
¶ Return a state dict that can be used to reset the state of the algorithm.
-
suggest
(num)[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
.