X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;ds=sidebyside;f=main.py;h=d194a8d2a27df44fabf7a0dadbeb05380819d9a2;hb=a8e608a50b84583ad624cdf69d7b34699557235b;hp=10c7b4991218a8d540fed20d6fd12169d71c9484;hpb=c32e471f8153ce4bdf19fb440f1e642eda4b972a;p=culture.git

diff --git a/main.py b/main.py
index 10c7b49..d194a8d 100755
--- a/main.py
+++ b/main.py
@@ -79,7 +79,9 @@ parser.add_argument("--dropout", type=float, default=0.1)
 
 parser.add_argument("--deterministic_synthesis", action="store_true", default=False)
 
-parser.add_argument("--reverse_cleanup", action="store_true", default=False)
+parser.add_argument("--reverse_cleanup", action="store_true", default=True)
+
+parser.add_argument("--validation_forward_only", action="store_true", default=False)
 
 parser.add_argument("--problem", type=str, default="sky")
 
@@ -362,7 +364,7 @@ def run_tests(model, quizz_machine, deterministic_synthesis):
 
             nb_test_samples += input.size(0)
 
-        main_test_accuracy = quizz_machine.produce_results(
+        model.main_test_accuracy = quizz_machine.produce_results(
             n_epoch=n_epoch,
             model=model,
             result_dir=args.result_dir,
@@ -373,8 +375,6 @@ def run_tests(model, quizz_machine, deterministic_synthesis):
 
         log_string(f"test_perplexity {n_epoch} {test_perplexity}")
 
-    model.main_test_accuracy = main_test_accuracy
-
 
 ######################################################################
 
@@ -395,8 +395,6 @@ def create_c_quizzes(
 ):
     recorded = []
 
-    sum_logits, sum_nb_c_quizzes = 0, 0
-
     nb_to_create = nb_for_train + nb_for_test
 
     # ------------------------------------------------------------
@@ -414,10 +412,9 @@ def create_c_quizzes(
             reverse_cleanup=args.reverse_cleanup,
         )
 
-        sum_logits += c_quizzes.size(0) * ave_seq_logproba
-        sum_nb_c_quizzes += c_quizzes.size(0)
-
-        nb_correct = quizz_machine.compute_correctness(c_quizzes, models)
+        nb_correct = quizz_machine.compute_correctness(
+            c_quizzes, models, both_directions=not args.validation_forward_only
+        )
 
         if args.dirty_debug:
             nb_correct = torch.randint(
@@ -435,13 +432,16 @@ def create_c_quizzes(
             f"keep c_quizzes kept {nv} nb_accumulated {nb_validated} / {nb_to_create}"
         )
 
-    # ------------------------------------------------------------
+    # store the new c_quizzes which have been validated
 
     new_c_quizzes = valid_c_quizzes(recorded, standard_validity)
 
     quizz_machine.store_c_quizzes(new_c_quizzes[:nb_for_train], for_train=True)
     quizz_machine.store_c_quizzes(new_c_quizzes[nb_for_train:], for_train=False)
 
+    # save a bunch of images to investigate what quizzes with a
+    # certain nb of correct predictions look like
+
     for n in range(len(models) + 1):
         s = (
             "_validated"
@@ -449,13 +449,12 @@ def create_c_quizzes(
             else ""
         )
 
-        quizz_machine.problem.save_quizzes(
-            valid_c_quizzes(recorded, criteria=lambda nb_correct: nb_correct == n)[:72],
-            args.result_dir,
-            f"culture_c_quiz_{n_epoch:04d}_N{n}{s}",
-        )
+        q = valid_c_quizzes(recorded, criteria=lambda nb_correct: nb_correct == n)[:72]
 
-    return sum_logits / sum_nb_c_quizzes
+        if q.size(0) > 0:
+            quizz_machine.save_quizzes(
+                args.result_dir, f"culture_c_quiz_{n_epoch:04d}_N{n}{s}", q
+            )
 
 
 ######################################################################
@@ -508,10 +507,10 @@ for n_epoch in range(args.nb_epochs):
         f"test_set_composition w_quizzes {quizz_machine.nb_batch_w_quizzes} c_quizzes {quizz_machine.nb_batch_c_quizzes}"
     )
 
-    cta = " ".join([f"{float(m.main_test_accuracy):.02f}" for m in models])
+    cta = " ".join([f"{float(m.main_test_accuracy):.04f}" for m in models])
     log_string(f"current_test_accuracies {cta}")
 
-    # replace a fraction of the w_quizzes with a fresh ones
+    # replace a fraction of the w_quizzes with fresh ones
     quizz_machine.renew_w_quizzes(args.nb_train_samples // args.nb_gpts)
 
     if min([m.main_test_accuracy for m in models]) >= args.accuracy_to_make_c_quizzes: