From b4c255babaae72d6a03b4c8e8e7e25f6ab0a19a0 Mon Sep 17 00:00:00 2001
From: Francois Fleuret <francois@fleuret.org>
Date: Wed, 27 Jul 2022 16:07:36 +0200
Subject: [PATCH] OCD cosmectics

---
 main.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/main.py b/main.py
index 76aeebd..77b1b22 100755
--- a/main.py
+++ b/main.py
@@ -212,10 +212,10 @@ class TaskPicoCLVR(Task):
     def vocabulary_size(self):
         return len(self.token2id)
 
-    def generate(self, descr_primer, model, nb_tokens):
+    def generate(self, primer_descr, model, nb_tokens):
         results = autoregression(
             model, self.batch_size,
-            1, nb_tokens, primer = descr2tensor(descr_primer),
+            1, nb_tokens, primer = descr2tensor(primer_descr),
             device = self.device
         )
         return ' '.join([ self.id2token[t.item()] for t in results.flatten() ])
@@ -226,7 +226,7 @@ class TaskPicoCLVR(Task):
         result_descr = [ ]
         nb_per_primer = 8
 
-        for descr_primer in [
+        for primer_descr in [
                 'red above green <sep> green top <sep> blue right of red <img>',
                 'there is red <sep> there is yellow <sep> there is blue <img>',
                 'red below yellow <sep> yellow below green <sep> green below blue <sep> red right <sep> yellow left <sep> green right <sep> blue left <img>',
@@ -234,7 +234,7 @@ class TaskPicoCLVR(Task):
         ]:
 
             for k in range(nb_per_primer):
-                result_descr.append(self.generate(descr_primer, model, nb_tokens))
+                result_descr.append(self.generate(primer_descr, model, nb_tokens))
 
         img = [ picoclvr.descr2img(d, height = self.height, width = self.width)
                 for d in result_descr ]
-- 
2.20.1