nip.parameters.agents.LrFactors#
- class nip.parameters.agents.LrFactors(actor: float = 1.0, critic: float = 1.0)[source]#
- Class representing learning rate factors for the actor and critic models. - actor(float)#
- Type:
- The learning rate factor for the actor model. 
 
 - critic(float)#
- Type:
- The learning rate factor for the critic model. 
 
 - Methods Summary - __eq__(other)- Return self==value. - __init__([actor, critic])- __repr__()- Return repr(self). - _get_param_class_from_dict(param_dict)- Try to get the parameter class from a dictionary of serialised parameters. - Construct a set of basic parameters for testing. - from_dict(params_dict[, ignore_extra_keys])- Create a parameters object from a dictionary. - get(address)- Get a value from the parameters object using a dot-separated address. - to_dict()- Convert the parameters object to a dictionary. - Attributes - Methods - __eq__(other)#
- Return self==value. 
 - __repr__()#
- Return repr(self). 
 - classmethod _get_param_class_from_dict(param_dict: dict) type[ParameterValue] | None[source]#
- Try to get the parameter class from a dictionary of serialised parameters. - Parameters:
- param_dict (dict) – A dictionary of parameters, which may have come from a - to_dictmethod. This dictionary may contain a- _typekey, which is used to determine the class of the parameter.
- Returns:
- param_class (type[ParameterValue] | None) – The class of the parameter, if it can be determined. 
- Raises:
- ValueError – If the class specified in the dictionary is not a valid parameter class. 
 
 - classmethod construct_test_params() BaseHyperParameters[source]#
- Construct a set of basic parameters for testing. 
 - classmethod from_dict(params_dict: dict, ignore_extra_keys: bool = False) BaseHyperParameters[source]#
- Create a parameters object from a dictionary.