Initial State, Save_Rate, and Final Results

README.md

@@ -37,5 +37,7 @@ games: number of games played per SPSA iteration, make sure this is a multiple o
 tc: The time control the matches are going to be played at. Increment is automatically `tc / 100`.
 
 threads: This corresponds to concurrency it cutechess, not the threads of the engine.
+
+save_rate: The number of games between times saving the state to a file
 ```
 

cutechess.json

@@ -4,5 +4,6 @@
     "games": 16,
     "tc": 5,
     "hash": 8,
-    "threads": 1
+    "threads": 1,
+    "save_rate": 10
 }

cutechess.py

@@ -19,7 +19,8 @@ def __init__(
         games: int = 120,
         tc: float = 5.0,
         hash: int = 8,
-        threads: int = 1
+        threads: int = 1,
+        save_rate: int = 10
     ):
         self.engine = engine
         self.book = book

main.py

@@ -65,6 +65,10 @@ def main():
 
     start_t = t
 
+    print("Initial state: ")
+    for param in spsa.params:
+        print(param)
+    print()
     try:
         while True:
             start = time.time()
@@ -73,14 +77,29 @@ def main():
 
             graph.update(spsa.t, copy.deepcopy(spsa.params))
             graph.save("graph.png")
+
+            if ((spsa.t / cutechess.games) % cutechess.save_rate) == 0:
+                print("Saving state...")
+                save_state(spsa)
+
+            print(
+                f"iterations: {spsa.t / cutechess.games} ({(avg_time / (spsa.t / cutechess.games - start_t)):.2f}s per iter)")
             print(
-                f"iterations: {spsa.t} ({(avg_time / (spsa.t - start_t)):.2f}s per iter)")
+                f"games: {spsa.t} ({(avg_time / (spsa.t - start_t)):.2f}s per game)")
             for param in spsa.params:
                 print(param)
             print()
     finally:
         print("Saving state...")
         save_state(spsa)
+        print("Final results: ")
+        print(
+            f"iterations: {spsa.t / cutechess.games} ({(avg_time / (spsa.t / cutechess.games - start_t)):.2f}s per iter)")
+        print(
+            f"games: {spsa.t} ({(avg_time / (spsa.t - start_t)):.2f}s per game)")
+        print("Final parameters: ")
+        for param in spsa.params:
+            print(param)
 
 
 if __name__ == "__main__":