fix tests

xopt-org · Sep 30, 2023 · e182f9d · e182f9d
1 parent 2b07505
commit e182f9d
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Showing 6 changed files with 0 additions and 21 deletions.
diff --git a/tests/generators/bayesian/test_bax.py b/tests/generators/bayesian/test_bax.py
@@ -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
 
@@ -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
 
@@ -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
 
@@ -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)
@@ -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)

diff --git a/tests/generators/bayesian/test_bayesian_exploration.py b/tests/generators/bayesian/test_bayesian_exploration.py
@@ -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
@@ -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
@@ -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

diff --git a/tests/generators/bayesian/test_expected_improvement.py b/tests/generators/bayesian/test_expected_improvement.py
@@ -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
@@ -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
@@ -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
 

diff --git a/tests/generators/bayesian/test_high_level.py b/tests/generators/bayesian/test_high_level.py
@@ -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
@@ -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:
@@ -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:
@@ -148,7 +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:
@@ -193,7 +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

diff --git a/tests/generators/bayesian/test_multi_fidelity.py b/tests/generators/bayesian/test_multi_fidelity.py
@@ -98,7 +98,6 @@ def test_generation(self):
 
         generator = MultiFidelityGenerator(vocs=vocs)
         generator.numerical_optimizer.n_restarts = 1
-        generator.numerical_optimizer.n_raw_samples = 1
 
         generator.add_data(data)
 

diff --git a/tests/generators/bayesian/test_upper_confidence_bound.py b/tests/generators/bayesian/test_upper_confidence_bound.py
@@ -22,7 +22,6 @@ def test_generate(self):
         gen = UpperConfidenceBoundGenerator(
             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
@@ -44,7 +43,6 @@ def test_cuda(self):
 
         if torch.cuda.is_available():
             gen.use_cuda = True
-            gen.numerical_optimizer.n_raw_samples = 1
             gen.numerical_optimizer.n_restarts = 1
             gen.n_monte_carlo_samples = 1
             gen.data = TEST_VOCS_DATA
@@ -58,7 +56,6 @@ def test_generate_w_overlapping_objectives_constraints(self):
         gen = UpperConfidenceBoundGenerator(
             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
@@ -71,7 +68,6 @@ def test_in_xopt(self):
         gen = UpperConfidenceBoundGenerator(
             vocs=TEST_VOCS_BASE,
         )
-        gen.numerical_optimizer.n_raw_samples = 1
         gen.numerical_optimizer.n_restarts = 1
         gen.n_monte_carlo_samples = 1