Added board-rep as cli argument, to state which input-board-rep to use.

Also fixed weird nesting of difference_in_values.

main.py

@@ -33,6 +33,9 @@ parser.add_argument('--list-models', action='store_true',
                     help='list all known models')
 parser.add_argument('--force-creation', action='store_true',
                     help='force model creation if model does not exist')
+parser.add_argument('--board-rep', action='store', dest='board_rep',
+                    default='tesauro',
+                    help='name of board representation to use as input to neural network')
 parser.add_argument('--use-baseline', action='store_true',
                     help='use the baseline model, note, has size 28')
 
@@ -55,7 +58,7 @@ config = {
     'train_perpetually': args.train_perpetually,
     'model_storage_path': 'models',
     'bench_storage_path': 'bench',
-    'board_representation': 'quack-fat',
+    'board_representation': args.board_rep,
     'force_creation': args.force_creation,
     'use_baseline': args.use_baseline
 }
@@ -83,6 +86,7 @@ def log_train_outcome(outcome, diff_in_values, trained_eps = 0, log_path = os.pa
                     'time': int(time.time()),
                     'average_diff_in_vals': diff_in_values/len(outcome)
     }
+
     with open(log_path, 'a+') as f:
         f.write("{time};{trained_eps};{count};{sum};{mean};{average_diff_in_vals}".format(**format_vars) + "\n")
     

network.py

@@ -582,6 +582,6 @@ class Network:
             
             writer.close()
         
-            return outcomes, difference_in_vals
+            return outcomes, difference_in_vals[0][0]