X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=80f2733c7a3e97d8c8f20a8df8d7a7ad674897bb;hb=1f6f5e352af881e57e26fa39ca5bf793c5d2c9c5;hp=003028a819ccc5e8882435dbb817ca59aa128ba0;hpb=5aee50805cfad1dd49bbf30b30fe65b05e03de78;p=picoclvr.git

diff --git a/main.py b/main.py
index 003028a..80f2733 100755
--- a/main.py
+++ b/main.py
@@ -125,7 +125,13 @@ parser.add_argument("--stack_fraction_values_for_train", type=float, default=0.7
 
 parser.add_argument("--expr_nb_variables", type=int, default=5)
 
-parser.add_argument("--expr_sequence_length", type=int, default=30)
+parser.add_argument("--expr_sequence_length", type=int, default=40)
+
+parser.add_argument("--expr_operand_max", type=int, default=9)
+
+parser.add_argument("--expr_result_max", type=int, default=99)
+
+parser.add_argument("--expr_input_file", type=str, default=None)
 
 ######################################################################
 
@@ -170,9 +176,9 @@ default_args = {
         "nb_test_samples": 1000,
     },
     "expr": {
-        "nb_epochs": 50,
+        "nb_epochs": 40,
         "batch_size": 25,
-        "nb_train_samples": 250000,
+        "nb_train_samples": 1000000,
         "nb_test_samples": 10000,
     },
 }
@@ -305,6 +311,8 @@ elif args.task == "expr":
         nb_test_samples=args.nb_test_samples,
         nb_variables=args.expr_nb_variables,
         sequence_length=args.expr_sequence_length,
+        operand_max=args.expr_operand_max,
+        result_max=args.expr_result_max,
         batch_size=args.batch_size,
         device=device,
     )
@@ -366,6 +374,20 @@ else:
 
 ######################################################################
 
+if args.task == "expr" and args.expr_input_file is not None:
+    task.produce_results(
+        nb_epochs_finished,
+        model,
+        args.result_dir,
+        log_string,
+        args.deterministic_synthesis,
+        args.expr_input_file,
+    )
+
+    exit(0)
+
+######################################################################
+
 nb_epochs = args.nb_epochs if args.nb_epochs > 0 else nb_epochs_default
 
 # Compute the entropy of the training tokens