From 1fe0529f4ac7cacfa8fced2885b7da1e639962a9 Mon Sep 17 00:00:00 2001
From: =?utf8?q?Fran=C3=A7ois=20Fleuret?= <francois@fleuret.org>
Date: Wed, 10 Jul 2024 16:40:51 +0200
Subject: [PATCH] Update.

---
 main.py         |  2 +-
 quiz_machine.py | 16 +++++++++++++---
 2 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/main.py b/main.py
index d400ab1..d2ac744 100755
--- a/main.py
+++ b/main.py
@@ -390,7 +390,7 @@ def create_c_quizzes(
             c_quizzes = c_quizzes[quiz_machine.non_trivial(c_quizzes)]
 
             if c_quizzes.size(0) > 0:
-                logproba = quiz_machine.logproba_solution(models, c_quizzes)
+                logproba = quiz_machine.logproba_of_solutions(models, c_quizzes)
                 for l in logproba:
                     s = " ".join([str(x.item()) for x in l])
                     logp_file.write(s + "\n")
diff --git a/quiz_machine.py b/quiz_machine.py
index cdfba85..34c09a7 100755
--- a/quiz_machine.py
+++ b/quiz_machine.py
@@ -285,6 +285,11 @@ class QuizMachine:
             predicted_answers,
         )
 
+    def vocabulary_size(self):
+        return self.nb_token_values
+
+    ######################################################################
+
     def batches(self, model, split="train", desc=None):
         assert split in {"train", "test"}
         if split == "train":
@@ -324,8 +329,7 @@ class QuizMachine:
         ):
             yield batch
 
-    def vocabulary_size(self):
-        return self.nb_token_values
+    ######################################################################
 
     def produce_results(
         self, n_epoch, model, result_dir, deterministic_synthesis, nmax=1000
@@ -400,6 +404,8 @@ class QuizMachine:
 
         return main_test_accuracy
 
+    ######################################################################
+
     def renew_w_quizzes(self, model, nb, for_train=True):
         input = model.train_w_quizzes if for_train else model.test_w_quizzes
         nb = min(nb, input.size(0))
@@ -408,13 +414,17 @@ class QuizMachine:
         self.reverse_random_half_in_place(fresh_w_quizzes)
         input[-nb:] = fresh_w_quizzes.to(self.device)
 
+    ######################################################################
+
     def store_c_quizzes(self, new_c_quizzes, for_train=True):
         if for_train:
             self.train_c_quizzes.append(new_c_quizzes)
         else:
             self.test_c_quizzes.append(new_c_quizzes)
 
-    def logproba_solution(self, models, c_quizzes):
+    ######################################################################
+
+    def logproba_of_solutions(self, models, c_quizzes):
         logproba = c_quizzes.new_zeros(c_quizzes.size(0), len(models))
 
         for model in models:
-- 
2.39.5