X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=main.py;h=5484f394f43e9cacdae499b1c1b48dfb771485eb;hb=eaed6307836d88abe7c0f4be733a38364ba20e2f;hp=d63398c1246158e4e8b7519366a7a4bd95ccd08d;hpb=d283cd3d46a6323fec4c6a0970ac71e553e4a486;p=culture.git

diff --git a/main.py b/main.py
index d63398c..5484f39 100755
--- a/main.py
+++ b/main.py
@@ -79,20 +79,26 @@ parser.add_argument("--dropout", type=float, default=0.1)
 
 parser.add_argument("--deterministic_synthesis", action="store_true", default=False)
 
-parser.add_argument("--both_directions", action="store_true", default=False)
+parser.add_argument("--bidirectional_validation", action="store_true", default=False)
 
 parser.add_argument("--problem", type=str, default="sky")
 
 parser.add_argument("--nb_gpts", type=int, default=5)
 
-parser.add_argument("--min_to_validate", type=int, default=4)
+parser.add_argument("--min_to_validate", type=int, default=None)
 
-parser.add_argument("--max_to_validate", type=int, default=4)
+parser.add_argument("--max_to_validate", type=int, default=None)
 
 parser.add_argument("--accuracy_to_make_c_quizzes", type=float, default=0.975)
 
 parser.add_argument("--dirty_debug", action="store_true", default=False)
 
+parser.add_argument("--generation_temperature", type=float, default=2.0)
+
+parser.add_argument("--deterministic_validation", action="store_true", default=False)
+
+######################################################################
+
 parser.add_argument("--sky_height", type=int, default=6)
 
 parser.add_argument("--sky_width", type=int, default=8)
@@ -107,6 +113,12 @@ parser.add_argument("--sky_speed", type=int, default=3)
 
 args = parser.parse_args()
 
+if args.min_to_validate is None:
+    args.min_to_validate = args = nb_gpts - 1
+
+if args.max_to_validate is None:
+    args.max_to_validate = args = nb_gpts - 1
+
 if args.result_dir is None:
     args.result_dir = f"results_culture"
 
@@ -362,6 +374,10 @@ def run_tests(model, quizz_machine, deterministic_synthesis):
 
             nb_test_samples += input.size(0)
 
+        test_perplexity = math.exp(min(100, acc_test_loss / nb_test_samples))
+
+        log_string(f"test_perplexity {n_epoch} {test_perplexity}")
+
         model.main_test_accuracy = quizz_machine.produce_results(
             n_epoch=n_epoch,
             model=model,
@@ -369,10 +385,6 @@ def run_tests(model, quizz_machine, deterministic_synthesis):
             deterministic_synthesis=deterministic_synthesis,
         )
 
-        test_perplexity = math.exp(min(100, acc_test_loss / nb_test_samples))
-
-        log_string(f"test_perplexity {n_epoch} {test_perplexity}")
-
 
 ######################################################################
 
@@ -401,33 +413,45 @@ def create_c_quizzes(
         nb_correct >= args.min_to_validate, nb_correct <= args.max_to_validate
     )
 
-    while valid_c_quizzes(recorded, standard_validity).size(0) < nb_to_create:
-        model_for_generation = models[torch.randint(len(models), (1,))]
+    file_name = os.path.join(args.result_dir, f"culture_c_quiz_{n_epoch:04d}_logp.dat")
+    with open(file_name, "w") as logp_file:
+        while valid_c_quizzes(recorded, standard_validity).size(0) < nb_to_create:
+            # Select a model at random to generate the new quizzes
 
-        c_quizzes, ave_seq_logproba = quizz_machine.generate_quizzes(
-            nb_to_create,
-            model_for_generation=model_for_generation,
-        )
+            model_for_generation = models[torch.randint(len(models), (1,))]
 
-        nb_correct = quizz_machine.compute_correctness(
-            c_quizzes, models, both_directions=args.both_directions
-        )
+            c_quizzes = quizz_machine.generate_quizzes(
+                nb_to_create,
+                model_for_generation=model_for_generation,
+                temperature=args.generation_temperature,
+            )
 
-        if args.dirty_debug:
-            nb_correct = torch.randint(
-                len(models) + 1, nb_correct.size(), device=c_quizzes.device
+            nb_correct, seq_logproba = quizz_machine.compute_correctness(
+                c_quizzes,
+                models,
+                bidirectional_validation=args.bidirectional_validation,
+                deterministic_validation=args.deterministic_validation,
             )
 
-        recorded.append((c_quizzes, nb_correct))
+            for n, l in zip(nb_correct, seq_logproba):
+                s = " ".join([str(x.item()) for x in l])
+                logp_file.write(f"{n} {s}\n")
 
-        nv = F.one_hot(nb_correct, num_classes=len(models) + 1).sum(0)
-        nv = " ".join([str(x.item()) for x in nv])
+            if args.dirty_debug:
+                nb_correct = torch.randint(
+                    len(models) + 1, nb_correct.size(), device=c_quizzes.device
+                )
 
-        nb_validated = valid_c_quizzes(recorded, standard_validity).size(0)
+            recorded.append((c_quizzes, nb_correct))
 
-        log_string(
-            f"keep c_quizzes model {model_for_generation.id} kept {nv} nb_accumulated {nb_validated} / {nb_to_create}"
-        )
+            nv = F.one_hot(nb_correct, num_classes=len(models) + 1).sum(0)
+            nv = " ".join([str(x.item()) for x in nv])
+
+            nb_validated = valid_c_quizzes(recorded, standard_validity).size(0)
+
+            log_string(
+                f"keep c_quizzes model {model_for_generation.id} kept {nv} nb_accumulated {nb_validated} / {nb_to_create}"
+            )
 
     # store the new c_quizzes which have been validated