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]¶
An algorithm that samples randomly from the problem’s space.
- Parameters
- space: `orion.algo.space.Space`
Optimisation space with priors for each dimension.
- seed: None, int or sequence of int
Seed for the random number generator used to sample new trials. Default:
None
- 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.