X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=9a3d34633bd88cff4ac1e05ee77989e4d725e7b1;hb=960c93d7c0aea41d180814c46d3a05686a426764;hp=af94979e937d852912dc79c01ada589436de461f;hpb=d2844d7a2d09ef38dc6f62d5e131059cccc872c5;p=picoclvr.git

diff --git a/main.py b/main.py
index af94979..9a3d346 100755
--- a/main.py
+++ b/main.py
@@ -33,7 +33,7 @@ parser.add_argument(
     "--task",
     type=str,
     default="sandbox",
-    help="sandbox, picoclvr, mnist, maze, snake, stack, expr, rpl, world",
+    help="byheart, learnop, guessop, twotargets, addition, picoclvr, mnist, maze, snake, stack, expr, rpl",
 )
 
 parser.add_argument("--log_filename", type=str, default="train.log", help=" ")
@@ -42,6 +42,10 @@ parser.add_argument("--result_dir", type=str, default=None)
 
 parser.add_argument("--seed", type=int, default=0)
 
+parser.add_argument("--max_percents_of_test_in_train", type=int, default=1)
+
+########################################
+
 parser.add_argument("--nb_epochs", type=int, default=None)
 
 parser.add_argument("--batch_size", type=int, default=None)
@@ -56,6 +60,8 @@ parser.add_argument("--learning_rate", type=float, default=1e-4)
 
 parser.add_argument("--learning_rate_schedule", type=str, default="10: 2e-5,30: 4e-6")
 
+########################################
+
 parser.add_argument("--model", type=str, default="37M")
 
 parser.add_argument("--dim_model", type=int, default=None)
@@ -70,6 +76,8 @@ parser.add_argument("--nb_blocks", type=int, default=None)
 
 parser.add_argument("--dropout", type=float, default=0.1)
 
+########################################
+
 parser.add_argument("--deterministic_synthesis", action="store_true", default=False)
 
 parser.add_argument("--no_checkpoint", action="store_true", default=False)
@@ -91,17 +99,6 @@ parser.add_argument("--rpl_nb_runs", type=int, default=8)
 
 parser.add_argument("--rpl_no_prog", action="store_true", default=False)
 
-##############################
-# sandbox options
-
-parser.add_argument("--sandbox_level", type=int, default=0)
-
-parser.add_argument("--sandbox_levels_nb_items", type=int, default=25)
-
-parser.add_argument("--sandbox_levels_len_source", type=int, default=6)
-
-parser.add_argument("--sandbox_levels_len_result", type=int, default=8)
-
 ##############################
 # picoclvr options
 
@@ -333,31 +330,52 @@ picoclvr_pruner_eval = (
 
 ######################################################################
 
-if args.task == "sandbox":
-    if args.sandbox_level == 0:
-        problem = problems.ProblemLevel0(
-            nb_sentences=args.sandbox_levels_nb_items,
-            len_prompt=args.sandbox_levels_len_source,
-            len_result=args.sandbox_levels_len_result,
-        )
-    elif args.sandbox_level == 1:
-        problem = problems.ProblemLevel1(
-            nb_operators=args.sandbox_levels_nb_items,
-            len_source=args.sandbox_levels_len_source,
-            len_result=args.sandbox_levels_len_result,
-        )
-    elif args.sandbox_level == 2:
-        problem = problems.ProblemLevel2(
-            len_source=args.sandbox_levels_len_source,
-            len_result=args.sandbox_levels_len_result,
-        )
-    else:
-        raise ValueError(f"Unknown sandbox level {args.sandbox_level}")
+if args.task == "byheart":
+    task = tasks.SandBox(
+        problem=problems.ProblemByHeart(),
+        nb_train_samples=args.nb_train_samples,
+        nb_test_samples=args.nb_test_samples,
+        batch_size=args.batch_size,
+        logger=log_string,
+        device=device,
+    )
+
+
+elif args.task == "learnop":
+    task = tasks.SandBox(
+        problem=problems.ProblemLearnOperator(),
+        nb_train_samples=args.nb_train_samples,
+        nb_test_samples=args.nb_test_samples,
+        batch_size=args.batch_size,
+        logger=log_string,
+        device=device,
+    )
+
+
+elif args.task == "guessop":
+    task = tasks.SandBox(
+        problem=problems.ProblemGuessOperator(),
+        nb_train_samples=args.nb_train_samples,
+        nb_test_samples=args.nb_test_samples,
+        batch_size=args.batch_size,
+        logger=log_string,
+        device=device,
+    )
+
+
+elif args.task == "twotargets":
+    task = tasks.SandBox(
+        problem=problems.ProblemTwoTargets(),
+        nb_train_samples=args.nb_train_samples,
+        nb_test_samples=args.nb_test_samples,
+        batch_size=args.batch_size,
+        logger=log_string,
+        device=device,
+    )
 
+elif args.task == "addition":
     task = tasks.SandBox(
-        # problem,
-        # problems.ProblemAddition(zero_padded=False, inverted_result=False),
-        problems.ProblemLenId(len_max=args.sandbox_levels_len_source),
+        problem=problems.ProblemAddition(),
         nb_train_samples=args.nb_train_samples,
         nb_test_samples=args.nb_test_samples,
         batch_size=args.batch_size,
@@ -570,8 +588,8 @@ log_string(
 )
 
 assert (
-    nb_in_train <= nb_test // 100
-), "More than 1% of test samples are in the train set"
+    nb_in_train <= args.max_percents_of_test_in_train * nb_test / 100
+), f"More than {args.max_percents_of_test_in_train}% of test samples are in the train set"
 
 ##############################