UniformIntegerParameterRange

class automation.UniformIntegerParameterRange()

Uniform randomly sampled integer Hyperparameter object.

Create a parameter to be sampled by the SearchStrategy.

• Parameters

  • name (str ) – The parameter name. Match the task hyper-parameter name.

  • min_value (int ) – The minimum sample to use for uniform random sampling.

  • max_value (int ) – The maximum sample to use for uniform random sampling.

  • step_size (int ) – The default step size is 1.

  • include_max_value (bool ) – Range includes the max_value.

    The values are:

    • True - Includes the max_value (Default)

    • False - Does not include.

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UniformIntegerParameterRange.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 ] ) –

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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.

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get_value

get_value()

Return uniformly sampled value based on object sampling definitions.

• Return type

  Mapping[str, Any]

• Returns

  {self.name: random value [self.min_value, self.max_value)}

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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

  ()

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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).

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to_list

to_list()

Return a list of all the valid values of the Parameter. If self.step_size is not defined, return 100 points between minmax values.

• Return type

  Sequence[Mapping[str, int]]

• Returns

  list of dicts {name: int}