[tune] lazy trials (#10802)

* Lazily fill trial queue

* Update interface

* Update end to end reporter test

* Removed `next_trials()` method

* Lint

* Print total number of samples to be generated in progress reporter. Allow infinite samples.

* Nit check

python/ray/tune/automl/search_policy.py

@@ -56,6 +56,8 @@ class AutoMLSearcher(SearchAlgorithm):
         self._unfinished_count = 0
         self._running_trials = {}
         self._completed_trials = {}
+        self._next_trials = []
+        self._next_trial_iter = None
 
         self._iteration = 0
         self._total_trial_num = 0
@@ -68,10 +70,27 @@ class AutoMLSearcher(SearchAlgorithm):
         """Returns the Trial object with the best reward_attr"""
         return self.best_trial
 
-    def next_trials(self):
+    def next_trial(self):
+        if not self._next_trial_iter:
+            self._generate_next_trials()
+            if not self._next_trials:
+                self.set_finished()
+                return None
+            self._next_trial_iter = iter(self._next_trials)
+
+        try:
+            return next(self._next_trial_iter)
+        except StopIteration:
+            self._next_trials = []
+            self._next_trial_iter = None
+            return None
+
+    def _generate_next_trials(self):
+        self._next_trials = []
+
         if self._unfinished_count > 0:
             # Last round not finished
-            return []
+            return
 
         trials = []
         raw_param_list, extra_arg_list = self._select()
@@ -110,7 +129,7 @@ class AutoMLSearcher(SearchAlgorithm):
                 "new": ntrial,
                 "total": self._total_trial_num
             })
-        return trials
+        self._next_trials = trials
 
     def on_trial_result(self, trial_id, result):
         if not result: