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enable xopt init from yaml file #151

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merged 14 commits into from
Oct 4, 2023
Merged

enable xopt init from yaml file #151

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0d131d0
enable xopt init from yaml file
roussel-ryan Sep 26, 2023
18c8677
start fixes to cnsga for yaml dumping
roussel-ryan Sep 27, 2023
d187cd0
mpi fixes + addition tests
roussel-ryan Sep 27, 2023
de3a8bd
formatting
roussel-ryan Sep 27, 2023
864741f
fix error with file inputs
roussel-ryan Sep 27, 2023
db267c6
Merge branch 'main' into new-xopt-init
roussel-ryan Sep 30, 2023
fdef0b8
fix validation issues in xopt base class and cnsga generator
roussel-ryan Sep 30, 2023
2b07505
formatting, remove n_raw_samples
roussel-ryan Sep 30, 2023
e182f9d
fix tests
roussel-ryan Sep 30, 2023
e77fa04
refactoring yaml and dumping methods
roussel-ryan Oct 1, 2023
6ae8dbc
update asynchronous CL interface keyword
roussel-ryan Oct 2, 2023
5171cb7
Working parallel notebook. Try tests.
ChristopherMayes Oct 2, 2023
c125353
black
ChristopherMayes Oct 2, 2023
9500441
CNSGA notebook
ChristopherMayes Oct 2, 2023
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1,877 changes: 394 additions & 1,483 deletions docs/examples/basic/xopt_parallel.ipynb
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282 changes: 218 additions & 64 deletions docs/examples/cnsga/cnsga_tnk.ipynb
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65 changes: 0 additions & 65 deletions docs/examples/cnsga/test.csv
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2 changes: 1 addition & 1 deletion scripts/execute_notebooks.bash
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@

NOTEBOOKS=$(find . -type f -name "*.ipynb" -not -path '*/.*')

SKIP="parallel"
SKIP="Xparallel"

echo $NOTEBOOKS

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5 changes: 0 additions & 5 deletions tests/generators/bayesian/test_bax.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,7 +115,6 @@ def test_generate(self):
vocs=test_vocs,
algorithm=alg,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.data = TEST_VOCS_DATA

Expand All @@ -128,7 +127,6 @@ def test_generate(self):
vocs=test_vocs,
algorithm=alg,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.data = TEST_VOCS_DATA

Expand All @@ -143,7 +141,6 @@ def test_cuda(self):
)

if torch.cuda.is_available():
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.data = TEST_VOCS_DATA

Expand All @@ -158,7 +155,6 @@ def test_in_xopt(self):
vocs=TEST_VOCS_BASE,
algorithm=alg,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1

xopt = Xopt(generator=gen, evaluator=evaluator, vocs=TEST_VOCS_BASE)
Expand All @@ -174,7 +170,6 @@ def test_file_saving(self):
gen = BaxGenerator(
vocs=TEST_VOCS_BASE, algorithm=alg, algorithm_results_file="test"
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1

xopt = Xopt(generator=gen, evaluator=evaluator, vocs=TEST_VOCS_BASE)
Expand Down
3 changes: 0 additions & 3 deletions tests/generators/bayesian/test_bayesian_exploration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,6 @@ def test_generate(self):
gen = BayesianExplorationGenerator(
vocs=ele,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.n_monte_carlo_samples = 1
gen.data = TEST_VOCS_DATA
Expand All @@ -34,7 +33,6 @@ def test_generate(self):
gen = BayesianExplorationGenerator(
vocs=ele,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.n_monte_carlo_samples = 1
gen.data = TEST_VOCS_DATA
Expand All @@ -47,7 +45,6 @@ def test_generate(self):
def test_in_xopt(self):
evaluator = Evaluator(function=xtest_callable)
gen = BayesianExplorationGenerator(vocs=TEST_VOCS_BASE)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.n_monte_carlo_samples = 1
gen.data = TEST_VOCS_DATA
Expand Down
4 changes: 1 addition & 3 deletions tests/generators/bayesian/test_custom_model.py
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Expand Up @@ -80,9 +80,7 @@ class ConstraintPrior(torch.nn.Module):
def forward(self, X):
return X.squeeze(dim=-1) ** 2

gp_constructor = StandardModelConstructor(
mean_modules={"c": ConstraintPrior()}
)
gp_constructor = StandardModelConstructor(mean_modules={"c": ConstraintPrior()})
generator = ExpectedImprovementGenerator(
vocs=my_vocs, gp_constructor=gp_constructor
)
Expand Down
3 changes: 0 additions & 3 deletions tests/generators/bayesian/test_expected_improvement.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,6 @@ def test_generate(self):
gen = ExpectedImprovementGenerator(
vocs=TEST_VOCS_BASE,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.n_monte_carlo_samples = 1
gen.data = TEST_VOCS_DATA
Expand All @@ -38,7 +37,6 @@ def test_generate_w_overlapping_objectives_constraints(self):
gen = ExpectedImprovementGenerator(
vocs=test_vocs,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.n_monte_carlo_samples = 1
gen.data = TEST_VOCS_DATA
Expand All @@ -51,7 +49,6 @@ def test_in_xopt(self):
gen = ExpectedImprovementGenerator(
vocs=TEST_VOCS_BASE,
)
gen.numerical_optimizer.n_raw_samples = 1
gen.numerical_optimizer.n_restarts = 1
gen.n_monte_carlo_samples = 1

Expand Down
23 changes: 12 additions & 11 deletions tests/generators/bayesian/test_high_level.py
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Original file line number Diff line number Diff line change
Expand Up @@ -48,7 +48,6 @@ def test_constrained_mobo(self):
numerical_optimizer:
name: LBFGS
n_restarts: 1
n_raw_samples: 2

evaluator:
function: xopt.resources.test_functions.tnk.evaluate_TNK
Expand All @@ -74,7 +73,6 @@ def test_mobo(self):
numerical_optimizer:
name: LBFGS
n_restarts: 2
n_raw_samples: 2
evaluator:
function: xopt.resources.test_functions.tnk.evaluate_TNK
vocs:
Expand All @@ -100,7 +98,6 @@ def test_restart_torch_inline_serialization(self):
numerical_optimizer:
name: LBFGS
n_restarts: 1
n_raw_samples: 2
evaluator:
function: xopt.resources.test_functions.tnk.evaluate_TNK
vocs:
Expand All @@ -125,10 +122,13 @@ def test_restart_torch_inline_serialization(self):
assert X2.generator.vocs.variable_names == ["x1", "x2"]
assert X2.generator.numerical_optimizer.n_restarts == 1
assert np.allclose(
X2.generator.data[X2.vocs.all_names].to_numpy(),
X.data[X.vocs.all_names].to_numpy()
X2.generator.data[X2.vocs.all_names].to_numpy(),
X.data[X.vocs.all_names].to_numpy(),
)
assert (
X.generator.model.state_dict().__str__()
== X2.generator.model.state_dict().__str__()
)
assert X.generator.model.state_dict().__str__() == X2.generator.model.state_dict().__str__()

X2.step()

Expand All @@ -145,7 +145,6 @@ def test_restart_torch_serialization(self):
numerical_optimizer:
name: LBFGS
n_restarts: 1
n_raw_samples: 2
evaluator:
function: xopt.resources.test_functions.tnk.evaluate_TNK
vocs:
Expand All @@ -171,7 +170,10 @@ def test_restart_torch_serialization(self):
X2.generator.data[X2.vocs.all_names].to_numpy(),
X.data[X.vocs.all_names].to_numpy(),
)
assert X.generator.model.state_dict().__str__() == X2.generator.model.state_dict().__str__()
assert (
X.generator.model.state_dict().__str__()
== X2.generator.model.state_dict().__str__()
)

X2.step()

Expand All @@ -187,7 +189,6 @@ def test_restart(self):
numerical_optimizer:
name: LBFGS
n_restarts: 1
n_raw_samples: 2

evaluator:
function: xopt.resources.test_functions.tnk.evaluate_TNK
Expand Down Expand Up @@ -218,10 +219,10 @@ def test_restart(self):

X2.step()

@pytest.fixture(scope='module', autouse=True)
@pytest.fixture(scope="module", autouse=True)
def clean_up(self):
yield
files = ['dump.yml', 'mobo_model.pt', 'dump_inline.yml']
files = ["dump.yml", "mobo_model.pt", "dump_inline.yml"]
for f in files:
if os.path.exists(f):
os.remove(f)
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