ParameterSet
class automation.ParameterSet()
Discrete randomly sampled Hyper-Parameter object.
Uniformly sample values form a list of discrete options (combinations) of parameters.
Parameters
parameter_combinations (list ) – The list/tuple of valid parameter combinations.
For example, two combinations with three specific parameters per combination:
[ {"opt1": 10, "arg2": 20, "arg2": 30},
{"opt2": 11, "arg2": 22, "arg2": 33} ]Two complex combination each one sampled from a different range:
[ {"opt1": UniformParameterRange('arg1',0,1) , "arg2": 20},
{"opt2": UniformParameterRange('arg1',11,12), "arg2": 22},]
ParameterSet.from_dict
classmethod from_dict(a_dict)
Construct Parameter object from a dict representation (deserialize from dict).
Return type
Parameter
Returns
The Parameter object.
Parameters
a_dict (Mapping [ str , str ] ) –
get_random_seed
static get_random_seed()
Get the global seed for all hyperparameter strategy random number sampling.
Return type
int
Returns
The random seed.
get_value
get_value()
Return uniformly sampled value from the valid list of values.
Return type
Mapping
[str
,Any
]Returns
{self.name: random entry from self.value}
set_random_seed
static set_random_seed(seed=1337)
Set global seed for all hyperparameter strategy random number sampling.
Parameters
seed (int ) – The random seed.
Return type
()
to_dict
to_dict()
Return a dict representation of the Parameter object. Used for serialization of the Parameter object.
Return type
Mapping
[str
,Union
[str
,Parameter
]]Returns
dict representation of the object (serialization).
to_list
to_list()
Return a list of all the valid values of the Parameter.
Return type
Sequence
[Mapping
[str
,Any
]]Returns
list of dicts {name: value}