add test_distribution.py

Author: SimonBlanke

tests/test_api/test_distribution.py

@@ -0,0 +1,104 @@
+import numpy as np
+from tqdm import tqdm
+
+from hyperactive.optimizers import HillClimbingOptimizer
+from hyperactive.experiment import BaseExperiment
+from hyperactive.search_config import SearchConfig
+
+
+class Experiment(BaseExperiment):
+    def objective_function(self, opt):
+        score = -opt["x1"] * opt["x1"]
+        return score
+
+
+experiment = Experiment()
+
+search_config = SearchConfig(
+    x1=list(np.arange(-100, 101, 1)),
+)
+
+n_iter = 15
+
+
+def test_n_jobs_0():
+    n_jobs = 2
+
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+    hyper.run()
+
+    assert len(hyper.search_data(experiment)) == n_iter * n_jobs
+
+
+def test_n_jobs_1():
+    n_jobs = 4
+
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=15, n_jobs=n_jobs)
+    hyper.run()
+
+    assert len(hyper.search_data(experiment)) == n_iter * n_jobs
+
+
+def test_n_jobs_2():
+    n_jobs = 8
+
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+    hyper.run()
+
+    assert len(hyper.search_data(experiment)) == n_iter * n_jobs
+
+
+def test_n_jobs_5():
+    n_jobs = 2
+
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+
+    hyper.run()
+
+    assert len(hyper.search_data(experiment)) == n_iter * n_jobs * 2
+
+
+def test_n_jobs_6():
+    n_jobs = 2
+
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+    hyper.add_search(experiment, search_config, n_iter=n_iter, n_jobs=n_jobs)
+
+    hyper.run()
+
+    assert len(hyper.search_data(experiment)) == n_iter * n_jobs * 4
+
+
+def test_n_jobs_7():
+    n_jobs = -1
+
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=15, n_jobs=n_jobs)
+    hyper.run()
+
+
+def test_multiprocessing_0():
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=15, n_jobs=2)
+    hyper.run(distribution="multiprocessing")
+
+
+def test_multiprocessing_1():
+    hyper = HillClimbingOptimizer()
+    hyper.add_search(experiment, search_config, n_iter=15, n_jobs=2)
+    hyper.run(
+        distribution={
+            "multiprocessing": {
+                "initializer": tqdm.set_lock,
+                "initargs": (tqdm.get_lock(),),
+            }
+        },
+    )