X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;ds=inline;f=quizz_machine.py;h=a3da36525c01fc49185f4d080f929e5162bd59f0;hb=b76e3f632315c63dbd8f11a53b187f23057e4e1f;hp=43fd868f229e8edb5aeb5d86742cdf564ce7f57b;hpb=6dbc18a5db82b12b06212841426896412e8bd6de;p=culture.git

diff --git a/quizz_machine.py b/quizz_machine.py
index 43fd868..a3da365 100755
--- a/quizz_machine.py
+++ b/quizz_machine.py
@@ -71,7 +71,7 @@ import sky
 
 class QuizzMachine:
     def save_image(self, input, result_dir, filename, logger):
-        img = sky.seq2img(input.to("cpu"), self.height, self.width)
+        img = self.sky.seq2img(input.to("cpu"))
         image_name = os.path.join(result_dir, filename)
         torchvision.utils.save_image(img.float() / 255.0, image_name, nrow=6, padding=4)
         logger(f"wrote {image_name}")
@@ -94,18 +94,12 @@ class QuizzMachine:
     ):
         super().__init__()
 
+        self.sky = sky.Sky(height=6, width=8, nb_birds=3, nb_iterations=2)
         self.batch_size = batch_size
         self.device = device
-        self.height = 6
-        self.width = 8
 
-        self.train_w_quizzes = sky.generate_seq(
-            nb_train_samples, height=self.height, width=self.width
-        ).to(device)
-
-        self.test_w_quizzes = sky.generate_seq(
-            nb_test_samples, height=self.height, width=self.width
-        ).to(device)
+        self.train_w_quizzes = self.sky.generate_seq(nb_train_samples).to(device)
+        self.test_w_quizzes = self.sky.generate_seq(nb_test_samples).to(device)
 
         self.nb_codes = max(self.train_w_quizzes.max(), self.test_w_quizzes.max()) + 1
 
@@ -234,9 +228,7 @@ class QuizzMachine:
         input = self.train_w_quizzes if for_train else self.test_w_quizzes
         nb = min(nb, input.size(0))
         input[:-nb] = input[nb:].clone()
-        input[-nb:] = sky.generate_seq(nb, height=self.height, width=self.width).to(
-            self.device
-        )
+        input[-nb:] = self.sky.generate_seq(nb).to(self.device)
 
     def store_c_quizzes(self, new_c_quizzes, for_train=True):
         if for_train:
@@ -258,7 +250,7 @@ class QuizzMachine:
         # Generate quizzes with model
 
         c_quizzes = torch.empty(
-            nb, self.height * self.width * 2 + 1, device=self.device, dtype=torch.int64
+            nb, self.train_w_quizzes.size(1), device=self.device, dtype=torch.int64
         )
 
         ar_mask = torch.full(c_quizzes.size(), 1, device=self.device)
@@ -306,11 +298,11 @@ class QuizzMachine:
         ###############################################################
         # Create the reverse quizzes
 
-        l = self.height * self.width
+        l = (c_quizzes.size(1) - 1) // 2
         direction = c_quizzes[:, l : l + 1]
-        direction = sky.token_forward * (
-            direction == sky.token_backward
-        ) + sky.token_backward * (direction == sky.token_forward)
+        direction = self.sky.token_forward * (
+            direction == self.sky.token_backward
+        ) + self.sky.token_backward * (direction == self.sky.token_forward)
         reverse_c_quizzes = torch.cat(
             [c_quizzes[:, l + 1 :], direction, c_quizzes[:, :l]], dim=1
         )