[tune] Rrk/sigopt_searcher_improvements (#10446)

python/ray/tune/suggest/sigopt.py

@@ -35,6 +35,10 @@ class SigOptSearch(Searcher):
         name (str): Name of experiment. Required by SigOpt.
         max_concurrent (int): Number of maximum concurrent trials supported
             based on the user's SigOpt plan. Defaults to 1.
+        connection (Connection): An existing connection to SigOpt.
+        observation_budget (int): Optional, can improve SigOpt performance.
+        project (str): Optional, Project name to assign this experiment to.
+            SigOpt can group experiments by project
         metric (str): The training result objective value attribute.
         mode (str): One of {min, max}. Determines whether objective is
             minimizing or maximizing the metric attribute.
@@ -71,15 +75,25 @@ class SigOptSearch(Searcher):
                  name="Default Tune Experiment",
                  max_concurrent=1,
                  reward_attr=None,
+                 connection=None,
+                 observation_budget=None,
+                 project=None,
                  metric="episode_reward_mean",
                  mode="max",
                  **kwargs):
-        assert sgo is not None, "SigOpt must be installed!"
         assert type(max_concurrent) is int and max_concurrent > 0
-        assert "SIGOPT_KEY" in os.environ, \
-            "SigOpt API key must be stored as environ variable at SIGOPT_KEY"
         assert mode in ["min", "max"], "`mode` must be 'min' or 'max'!"
 
+        if connection is not None:
+            self.conn = connection
+        else:
+            assert sgo is not None, "SigOpt must be installed!"
+            assert "SIGOPT_KEY" in os.environ, \
+                "SigOpt API key must be stored as " \
+                "environ variable at SIGOPT_KEY"
+            # Create a connection with SigOpt API, requires API key
+            self.conn = sgo.Connection(client_token=os.environ["SIGOPT_KEY"])
+
         self._max_concurrent = max_concurrent
         self._metric = metric
         if mode == "max":
@@ -88,18 +102,25 @@ class SigOptSearch(Searcher):
             self._metric_op = -1.
         self._live_trial_mapping = {}
 
-        # Create a connection with SigOpt API, requires API key
-        self.conn = sgo.Connection(client_token=os.environ["SIGOPT_KEY"])
-
-        self.experiment = self.conn.experiments().create(
+        sigopt_params = dict(
             name=name,
             parameters=space,
-            parallel_bandwidth=self._max_concurrent,
-        )
+            parallel_bandwidth=self._max_concurrent)
+
+        if observation_budget is not None:
+            sigopt_params["observation_budget"] = observation_budget
+
+        if project is not None:
+            sigopt_params["project"] = project
+
+        self.experiment = self.conn.experiments().create(**sigopt_params)
 
         super(SigOptSearch, self).__init__(metric=metric, mode=mode, **kwargs)
 
     def suggest(self, trial_id):
+        if self._max_concurrent:
+            if len(self._live_trial_mapping) >= self._max_concurrent:
+                return None
         # Get new suggestion from SigOpt
         suggestion = self.conn.experiments(
             self.experiment.id).suggestions().create()