Update.

diff --git a/main.py b/main.py
index af94979..68b946a 100755 (executable)
--- a/main.py
+++ b/main.py
@@ -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)
@@ -570,8 +578,8 @@ 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"
 
 ##############################
 

diff --git a/problems.py b/problems.py
index dca201f..7b1d698 100755 (executable)
--- a/problems.py
+++ b/problems.py
@@ -21,6 +21,38 @@ class Problem:
 ####################
 
 
+class ProblemTwoTargets(Problem):
+    def __init__(self, len_total=10, len_target=2):
+        assert len_total >= 3 * (2 + len_target) - 1
+        self.len_total = len_total
+        self.len_target = len_target
+
+    def generate_sequences(self, nb):
+        k = torch.arange(self.len_total)[None, :]
+        l = torch.randint(self.len_total, (2, nb))[:, :, None] + 1
+        i = torch.randint(10, (2, nb))[:, :, None]
+        a = l[0]
+        b = l[0] + 1 + l[1]
+        c = l[0] + 1 + l[1] + 1 + l[0]
+        sequences = (
+            (k < a) * i[0]
+            + (k == a) * 10
+            + (k > a) * (k < b) * i[1]
+            + (k == b) * 11
+            + (k > b) * (k < c) * i[1]
+            + (k >= c) * 12
+        )
+        ar_mask = (sequences == 11).long()
+        ar_mask = (ar_mask.cumsum(1) - ar_mask).clamp(max=1)
+        return sequences, ar_mask
+
+    def seq2str(self, seq):
+        return "".join("0123456789|>_"[x.item()] for x in seq)
+
+
+####################
+
+
 class ProblemLenId(Problem):
     def __init__(self, len_max=10):
         self.len_max = len_max