lava.lib.optimization.problems.bayesian

lava.lib.optimization.problems.bayesian.models

class lava.lib.optimization.problems.bayesian.models.PyDualInputFunctionModel(proc_params=None)

Bases: PyLoihiProcessModel

A Python-based implementation of the DualInputFunction process that represents a dual continuous input, single output, non-linear objective function.

implements_process

alias of DualInputFunction

implements_protocol

alias of LoihiProtocol

num_objectives = LavaPyType(cls=<class 'int'>, d_type=<class 'int'>, precision=None)

num_params = LavaPyType(cls=<class 'int'>, d_type=<class 'int'>, precision=None)

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

run_spk()

tick the model forward by one time-step

Return type

None

tags: ty.List[str] = ['floating_pt']

x_in: PyInPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyInPortVectorDense'>, d_type=<class 'numpy.float64'>, precision=None)

y_out: PyOutPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'numpy.float64'>, precision=None)

class lava.lib.optimization.problems.bayesian.models.PySingleInputFunctionModel(proc_params=None)

Bases: PyLoihiProcessModel

A Python-based implementation of the SingleInput process that represents a single input/output non-linear objective function.

implements_process

alias of SingleInputFunction

implements_protocol

alias of LoihiProtocol

num_objectives = LavaPyType(cls=<class 'int'>, d_type=<class 'int'>, precision=None)

num_params = LavaPyType(cls=<class 'int'>, d_type=<class 'int'>, precision=None)

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

run_spk()

tick the model forward by one time-step

Return type

None

tags: ty.List[str] = ['floating_pt']

x_in: PyInPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyInPortVectorDense'>, d_type=<class 'numpy.float64'>, precision=None)

y_out: PyOutPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'numpy.float64'>, precision=None)

lava.lib.optimization.problems.bayesian.processes

class lava.lib.optimization.problems.bayesian.processes.BaseObjectiveFunction(num_params, num_objectives, **kwargs)

Bases: AbstractProcess

A base objective function process that shall be used as the basis of all black-box processes.

class lava.lib.optimization.problems.bayesian.processes.DualInputFunction(**kwargs)

Bases: BaseObjectiveFunction

An abstract process representing a dual input, single output test function.

class lava.lib.optimization.problems.bayesian.processes.SingleInputFunction(**kwargs)

Bases: BaseObjectiveFunction

An abstract process representing a single input/output test function.