def test_get_set_params_base_step():
s = SomeStep()
s.set_params(learning_rate=0.1)
hyperparams = s.get_params()
assert hyperparams == {"learning_rate": 0.1}
def test_pipeline_should_update_hyperparams_space():
p = Pipeline([
SomeStep().set_name('step_1'),
SomeStep().set_name('step_2')
])
p.set_hyperparams_space({
'hp': RandInt(1, 2),
'step_1__hp': RandInt(2, 3),
'step_2__hp': RandInt(3, 4)
})
p.update_hyperparams_space({
'hp': RandInt(4, 6),
'step_2__hp': RandInt(6, 8)
})
assert isinstance(p.hyperparams_space, HyperparameterSpace)
assert p.hyperparams_space['hp'].min_included == 4
assert p.hyperparams_space['hp'].max_included == 6
assert p[0].hyperparams_space['hp'].min_included == 2
assert p[0].hyperparams_space['hp'].max_included == 3
assert p[1].hyperparams_space['hp'].min_included == 6
assert p[1].hyperparams_space['hp'].max_included == 8
def test_pipeline_should_set_hyperparams():
p = Pipeline([
SomeStep().set_name('step_1'),
SomeStep().set_name('step_2')
])
p.set_hyperparams({
'hp': 1,
'step_1__hp': 2,
'step_2__hp': 3
})
assert isinstance(p.hyperparams, HyperparameterSamples)
assert p.hyperparams['hp'] == 1
assert p[0].hyperparams['hp'] == 2
assert p[1].hyperparams['hp'] == 3
def test_meta_step_mixin_should_set_hyperparams_space():
p = SomeMetaStepMixin(SomeStep())
p.set_hyperparams_space(HyperparameterSpace({
META_STEP_HP: RAND_INT_META_STEP,
SOME_STEP_HP: RAND_INT_SOME_STEP
}))
assert p.hyperparams_space[META_STEP_HP] == RAND_INT_META_STEP
assert p.get_step().hyperparams_space[SOME_STEP_HP_KEY] == RAND_INT_SOME_STEP
def test_step_cloner_should_set_steps_hyperparams_space():
p = StepClonerForEachDataInput(SomeStep())
p.set_hyperparams_space(HyperparameterSpace({
META_STEP_HP: RAND_INT_STEP_CLONER,
SOME_STEP_HP: RAND_INT_SOME_STEP
}))
assert isinstance(p.get_step().hyperparams_space, HyperparameterSpace)
assert p.get_step().hyperparams_space[SOME_STEP_HP_KEY] == RAND_INT_SOME_STEP
def test_step_cloner_should_set_hyperparams():
p = StepClonerForEachDataInput(SomeStep())
p.set_hyperparams(HyperparameterSamples({
META_STEP_HP: META_STEP_HP_VALUE,
SOME_STEP_HP: SOME_STEP_HP_VALUE
}))
assert isinstance(p.hyperparams, HyperparameterSamples)
assert p.hyperparams[META_STEP_HP] == META_STEP_HP_VALUE
assert p.get_step().get_hyperparams()[SOME_STEP_HP_KEY] == SOME_STEP_HP_VALUE
def test_step_cloner_should_get_hyperparams():
p = StepClonerForEachDataInput(SomeStep())
p.set_hyperparams(HyperparameterSamples({
META_STEP_HP: META_STEP_HP_VALUE,
SOME_STEP_HP: SOME_STEP_HP_VALUE
}))
hyperparams = p.get_hyperparams()
assert hyperparams[META_STEP_HP] == META_STEP_HP_VALUE
assert hyperparams[SOME_STEP_HP] == SOME_STEP_HP_VALUE
def test_meta_step_mixin_should_set_hyperparams():
p = SomeMetaStepMixin(SomeStep())
p.set_hyperparams(HyperparameterSamples({
META_STEP_HP: META_STEP_HP_VALUE,
SOME_STEP_HP: SOME_STEP_HP_VALUE
}))
assert isinstance(p.hyperparams, HyperparameterSamples)
assert p.hyperparams[META_STEP_HP] == META_STEP_HP_VALUE
assert p.get_step().get_hyperparams()['somestep_hyperparam'] == SOME_STEP_HP_VALUE
def test_meta_step_mixin_should_get_hyperparams():
p = SomeMetaStepMixin(SomeStep())
p.set_hyperparams(HyperparameterSamples({
META_STEP_HP: META_STEP_HP_VALUE,
SOME_STEP_HP: SOME_STEP_HP_VALUE
}))
hyperparams = p.get_hyperparams()
assert hyperparams[META_STEP_HP] == META_STEP_HP_VALUE
assert hyperparams[SOME_STEP_HP] == SOME_STEP_HP_VALUE
def test_step_cloner_should_get_hyperparams_space():
p = StepClonerForEachDataInput(SomeStep())
p.set_hyperparams_space(HyperparameterSpace({
META_STEP_HP: RAND_INT_STEP_CLONER,
SOME_STEP_HP: RAND_INT_SOME_STEP
}))
hyperparams_space = p.get_hyperparams_space()
assert hyperparams_space[META_STEP_HP] == RAND_INT_STEP_CLONER
assert hyperparams_space[SOME_STEP_HP] == RAND_INT_SOME_STEP
def test_step_cloner_should_set_steps_hyperparams():
p = StepClonerForEachDataInput(SomeStep())
p.fit_transform([[0, 0]])
p.set_hyperparams(
HyperparameterSamples({
META_STEP_HP: META_STEP_HP_VALUE,
SOME_STEP_HP: SOME_STEP_HP_VALUE
}))
assert isinstance(p.hyperparams, HyperparameterSamples)
assert isinstance(p.steps[0].hyperparams, HyperparameterSamples)
assert p.steps[0].get_hyperparams()[SOME_STEP_HP_KEY] == SOME_STEP_HP_VALUE
def test_meta_step_mixin_update_hyperparams_should_update_wrapped_step_hyperparams():
p = SomeMetaStepMixin(SomeStep())
p.set_hyperparams(HyperparameterSamples({
META_STEP_HP: META_STEP_HP_VALUE,
SOME_STEP_HP: SOME_STEP_HP_VALUE
}))
p.update_hyperparams(HyperparameterSamples({
SOME_STEP_HP: SOME_STEP_HP_VALUE + 1
}))
assert p.hyperparams[META_STEP_HP] == META_STEP_HP_VALUE
assert p.get_step().get_hyperparams()['somestep_hyperparam'] == SOME_STEP_HP_VALUE + 1
def test_meta_step_mixin_update_hyperparams_space_should_update_wrapped_step_hyperparams():
p = SomeMetaStepMixin(SomeStep())
p.set_hyperparams_space(HyperparameterSpace({
META_STEP_HP: RAND_INT_META_STEP,
SOME_STEP_HP: RAND_INT_SOME_STEP
}))
updated_some_step_hp_space = RandInt(0, 100)
p.update_hyperparams_space(HyperparameterSpace({
SOME_STEP_HP: updated_some_step_hp_space
}))
assert p.hyperparams_space[META_STEP_HP] == RAND_INT_META_STEP
assert p.wrapped.get_hyperparams_space()['somestep_hyperparam'] == updated_some_step_hp_space
def test_pipeline_should_get_hyperparams_space():
p = Pipeline([
SomeStep().set_name('step_1'),
SomeStep().set_name('step_2')
])
p.set_hyperparams_space({
'hp': RandInt(1, 2),
'step_1__hp': RandInt(2, 3),
'step_2__hp': RandInt(3, 4)
})
hyperparams_space = p.get_hyperparams_space()
assert isinstance(hyperparams_space, HyperparameterSpace)
assert hyperparams_space['hp'].min_included == 1
assert hyperparams_space['hp'].max_included == 2
assert hyperparams_space['step_1__hp'].min_included == 2
assert hyperparams_space['step_1__hp'].max_included == 3
assert hyperparams_space['step_2__hp'].min_included == 3
assert hyperparams_space['step_2__hp'].max_included == 4
def test_step_cloner_update_hyperparams_space_should_update_wrapped_step_hyperparams():
p = StepClonerForEachDataInput(SomeStep())
p.set_hyperparams_space(HyperparameterSpace({
META_STEP_HP: RAND_INT_META_STEP,
SOME_STEP_HP: RAND_INT_SOME_STEP
}))
updated_some_step_hp_space = RandInt(0, 400)
p.update_hyperparams_space(HyperparameterSpace({
SOME_STEP_HP: updated_some_step_hp_space
}))
assert isinstance(p.hyperparams, HyperparameterSamples)
assert p.hyperparams_space[META_STEP_HP] == RAND_INT_META_STEP
assert p.wrapped.get_hyperparams_space()[SOME_STEP_HP_KEY] == updated_some_step_hp_space
def __init__(self):
SomeStep.__init__(self)
self.called_with = None
