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Add TPE algorithm into Orion #381

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Merged
merged 9 commits into from
Apr 30, 2020
Merged

Add TPE algorithm into Orion #381

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f238a75
add tpe algorithm
donglinjy Apr 11, 2020
4a6d866
miss one function doc
donglinjy Apr 12, 2020
e9445d9
refine some code for tpe
donglinjy Apr 23, 2020
b0e4467
update test cases
donglinjy Apr 28, 2020
450c782
remove print
donglinjy Apr 28, 2020
c872738
expose full weight number as parameter
donglinjy Apr 28, 2020
f2e6b66
Merge branch 'develop' into tpe-algo
bouthilx Apr 30, 2020
c5473ca
refine weight normalization
donglinjy Apr 30, 2020
e2f28dd
Merge branch 'tpe-algo' of https://github.com/donglinjy/orion into tp…
donglinjy Apr 30, 2020
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2 changes: 2 additions & 0 deletions tests/functional/algos/test_algos.py
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Expand Up @@ -73,6 +73,8 @@ def test_simple(monkeypatch, config_file):
@pytest.mark.usefixtures("null_db_instances")
def test_random_stop(monkeypatch):
"""Test a simple usage scenario."""
# TODO: TPE should support this case once discrete is added,
# then parametrized config_file should be used
config_file = 'random_config.yaml'
monkeypatch.chdir(os.path.dirname(os.path.abspath(__file__)))
orion.core.cli.main(["hunt", "--config", config_file,
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9 changes: 6 additions & 3 deletions tests/unittests/algo/test_tpe.py
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Expand Up @@ -85,9 +85,12 @@ def test_adaptive_parzen_normal_estimator_weight():
# prior weight
mus, sigmas, weights = adaptive_parzen_estimator(obs_mus, low, high, prior_weight=0.5,
equal_weight=False, flat_num=25)
print(weights)
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Left-over print. :)

prior_pos = numpy.searchsorted(mus, 2)
assert numpy.all(weights[:30 - 25] == (numpy.linspace(1.0 / 30, 1.0, num=30 - 25) / 31))
assert numpy.all(weights[33 - 25:prior_pos] == 1 / 31)
assert weights[prior_pos] == 0.5 / 31
assert numpy.all(weights[31 - prior_pos:] == weights[-1])
assert numpy.all(weights[prior_pos + 1:] == 1 / 31)
assert numpy.all(sigmas == 6 / 10)


Expand Down Expand Up @@ -170,7 +173,7 @@ def test_sample(self, tpe):
def test_get_loglikelis(self):
"""Test to get log likelis of points"""
mus = numpy.linspace(-10, 10, num=10, endpoint=False)
weights = [0.009, 0.006, 0.1, 0.02, 0.004, 0.26, 0.04, 0.5, 0.06, 0.001]
weights = [0.009, 0.006, 0.1, 0.02, 0.003, 0.26, 0.04, 0.5, 0.061, 0.001]

sigmas = [0.00001] * 10
gmm_sampler = GMMSampler(tpe, mus, sigmas, -11, 9, weights)
Expand Down Expand Up @@ -256,7 +259,7 @@ def test_unsupported_space(self):
assert 'TPE now only supports 1D shape' in str(ex.value)

def test_split_trials(self, tpe):
"""Test observed trails can be split based on TPE gamma"""
"""Test observed trials can be split based on TPE gamma"""
space = Space()
dim1 = Real('yolo1', 'uniform', -3, 6)
space.register(dim1)
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