[Tune] Add ZOOpt search algorithm (#7960)

* add zoopt * add zoopt search algo * add zoopt * fix zoopt * add zoopt requirements * fix zoopt * remove generated guides * Apply suggestions from code review Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
2026-07-27 11:26:41 +08:00 · 2020-04-15 21:13:29 -07:00
parent 956ea7c944
commit 5c274fe631
7 changed files with 309 additions and 2 deletions
@@ -0,0 +1,65 @@
+"""This test checks that ZOOpt is functional.
+
+It also checks that it is usable with a separate scheduler.
+"""
+
+import ray
+from ray.tune import run
+from ray.tune.suggest.zoopt import ZOOptSearch
+from ray.tune.schedulers import AsyncHyperBandScheduler
+from zoopt import ValueType
+
+
+def easy_objective(config, reporter):
+    import time
+    time.sleep(0.2)
+    for i in range(config["iterations"]):
+        reporter(
+            timesteps_total=i,
+            mean_loss=(config["height"] - 14)**2 - abs(config["width"] - 3))
+        time.sleep(0.02)
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--smoke-test", action="store_true", help="Finish quickly for testing")
+    args, _ = parser.parse_known_args()
+    ray.init()
+
+    # This dict could mix continuous dimensions and discrete dimensions,
+    # for example:
+    dim_dict = {
+        # for continuous dimensions: (continuous, search_range, precision)
+        "height": (ValueType.CONTINUOUS, [-10, 10], 1e-2),
+        # for discrete dimensions: (discrete, search_range, has_order)
+        "width": (ValueType.DISCRETE, [-10, 10], False)
+    }
+
+    config = {
+        "num_samples": 200 if args.smoke_test else 1000,
+        "config": {
+            "iterations": 10,  # evaluation times
+        },
+        "stop": {
+            "timesteps_total": 10  # cumstom stop rules
+        }
+    }
+
+    zoopt_search = ZOOptSearch(
+        algo="Asracos",  # only support ASRacos currently
+        budget=config["num_samples"],
+        dim_dict=dim_dict,
+        max_concurrent=4,
+        metric="mean_loss",
+        mode="min")
+
+    scheduler = AsyncHyperBandScheduler(metric="mean_loss", mode="min")
+
+    run(easy_objective,
+        search_alg=zoopt_search,
+        name="zoopt_search",
+        scheduler=scheduler,
+        **config)