X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=15e6d99fc97f821afc8b54d166fd01c2af6978dc;hb=667ef70b1f185c7bbd66d7782fbde39fff093ba9;hp=35bf02c0123815b31d479df63f935839c7523b33;hpb=02b0a7bb770f07f2e91f1c77b899815516087b6a;p=picoclvr.git

diff --git a/main.py b/main.py
index 35bf02c..15e6d99 100755
--- a/main.py
+++ b/main.py
@@ -1030,8 +1030,9 @@ class TaskExpr(Task):
         train_sequences = expr.generate_sequences(
             nb_train_samples,
             nb_variables=nb_variables,
-            length=2 * sequence_length,
-            randomize_length=True,
+            length=sequence_length,
+            # length=2 * sequence_length,
+            # randomize_length=True,
         )
         test_sequences = expr.generate_sequences(
             nb_test_samples,
@@ -1115,6 +1116,28 @@ class TaskExpr(Task):
                 nb_total = input.size(0)
                 nb_correct = (input == result).long().min(1).values.sum()
 
+                #######################################################################
+                # Comput predicted vs. true variable values
+
+                values_input = expr.extract_results([self.seq2str(s) for s in input])
+                max_input = max([max(x.values()) for x in values_input])
+                values_result = expr.extract_results([self.seq2str(s) for s in result])
+                max_result = max(
+                    [-1 if len(x) == 0 else max(x.values()) for x in values_result]
+                )
+
+                nb_missing = torch.zeros(max_input + 1)
+                nb_predicted = torch.zeros(max_input + 1, max_result + 1)
+
+                for i, r in zip(values_input, values_result):
+                    for n, vi in i.items():
+                        vr = r.get(n)
+                        if vr is None or vr < 0:
+                            nb_missing[vi] += 1
+                        else:
+                            nb_predicted[vi, vr] += 1
+                ######################################################################
+
                 return nb_total, nb_correct
 
             test_nb_total, test_nb_correct = compute_nb_correct(self.test_input[:1000])