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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 hyper-parameter 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 hyper-parameter 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}