matchzoo.engine.param
¶
Parameter class.
Module Contents¶
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matchzoo.engine.param.
SpaceType
¶
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class
matchzoo.engine.param.
Param
(name: str, value: typing.Any = None, hyper_space: typing.Optional[SpaceType] = None, validator: typing.Optional[typing.Callable[[typing.Any], bool]] = None, desc: typing.Optional[str] = None)¶ Bases:
object
Parameter class.
Basic usages with a name and value:
>>> param = Param('my_param', 10) >>> param.name 'my_param' >>> param.value 10
Use with a validator to make sure the parameter always keeps a valid value.
>>> param = Param( ... name='my_param', ... value=5, ... validator=lambda x: 0 < x < 20 ... ) >>> param.validator # doctest: +ELLIPSIS <function <lambda> at 0x...> >>> param.value 5 >>> param.value = 10 >>> param.value 10 >>> param.value = -1 Traceback (most recent call last): ... ValueError: Validator not satifised. The validator's definition is as follows: validator=lambda x: 0 < x < 20
Use with a hyper space. Setting up a hyper space for a parameter makes the parameter tunable in a
matchzoo.engine.Tuner
.>>> from matchzoo.engine.hyper_spaces import quniform >>> param = Param( ... name='positive_num', ... value=1, ... hyper_space=quniform(low=1, high=5) ... ) >>> param.hyper_space # doctest: +ELLIPSIS <matchzoo.engine.hyper_spaces.quniform object at ...> >>> from hyperopt.pyll.stochastic import sample >>> hyperopt_space = param.hyper_space.convert(param.name) >>> samples = [sample(hyperopt_space) for _ in range(64)] >>> set(samples) == {1, 2, 3, 4, 5} True
The boolean value of a
Param
instance is only True when the value is not None. This is because some default falsy values like zero or an empty list are valid parameter values. In other words, the boolean value means to be “if the parameter value is filled”.>>> param = Param('dropout') >>> if param: ... print('OK') >>> param = Param('dropout', 0) >>> if param: ... print('OK') OK
A _pre_assignment_hook is initialized as a data type convertor if the value is set as a number to keep data type consistency of the parameter. This conversion supports python built-in numbers, numpy numbers, and any number that inherits
numbers.Number
.>>> param = Param('float_param', 0.5) >>> param.value = 10 >>> param.value 10.0 >>> type(param.value) <class 'float'>
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name
:str¶ Name of the parameter.
Type: return
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value
:typing.Any¶ Value of the parameter.
Type: return
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hyper_space
:SpaceType¶ Hyper space of the parameter.
Type: return
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validator
:typing.Callable[[typing.Any], bool]¶ Validator of the parameter.
Type: return
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desc
:str¶ Parameter description.
Type: return
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_infer_pre_assignment_hook
(self)¶
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_validate
(self, value)¶
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__bool__
(self)¶ Returns: False when the value is None, True otherwise.
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set_default
(self, val, verbose=1)¶ Set default value, has no effect if already has a value.
Parameters: - val – Default value to set.
- verbose – Verbosity.
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reset
(self)¶ Set the parameter’s value to None, which means “not set”.
This method bypasses validator.
Example
>>> import matchzoo as mz >>> param = mz.Param( ... name='str', validator=lambda x: isinstance(x, str)) >>> param.value = 'hello' >>> param.value = None Traceback (most recent call last): ... ValueError: Validator not satifised. The validator's definition is as follows: name='str', validator=lambda x: isinstance(x, str)) >>> param.reset() >>> param.value is None True
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