def test_hyperband(tmpdir):
TUNE_OBJECT_FACTORY.set_temp_path(str(tmpdir))
space = keras_space(MockSpec, l1=RandInt(8, 16), l2=RandInt(8, 24))
with raises(TuneCompileError):
suggest_keras_models_by_hyperband(
space,
plans=[
[(2.0, 4), (4.0, 2)],
[(4.0, 2), (2.0, 4)],
],
)
space = space.sample(10, 0)
reports = suggest_keras_models_by_hyperband(
space,
plans=[
[(2.0, 4), (4.0, 2)],
[(4.0, 2), (2.0, 4)],
],
top_n=2,
)
for r in reports:
print(r)
assert 2 == len(reports)
def test_sha(tmpdir):
TUNE_OBJECT_FACTORY.set_temp_path(str(tmpdir))
space = keras_space(MockSpec, l1=RandInt(8, 16), l2=RandInt(8, 24))
with raises(TuneCompileError):
suggest_keras_models_by_sha(space, plan=[(2.0, 4), (4.0, 2)])
space = space.sample(6, 0)
reports = suggest_keras_models_by_sha(space, plan=[(2.0, 4), (4.0, 2)], top_n=2)
for r in reports:
print(r.jsondict)
assert 2 == len(reports)
def test_objective():
def validate(reports):
assert reports[-1].metric < 15
space = keras_space(MockSpec, l1=16, l2=16)
obj = KerasObjective(_TYPE_DICT)
for cont in [True, False]:
validate_iterative_objective(
obj,
Trial("a", params=list(space)[0]),
budgets=[3, 3, 4],
continuous=cont,
validator=validate,
)