From: Francois Fleuret <francois@fleuret.org>
Date: Sat, 9 Jun 2018 12:11:24 +0000 (+0200)
Subject: Update.
X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=0a30c677bfb0aac1f9eebc9646728519ca72bf5b;p=pytorch.git

Update.
---

diff --git a/ae_size.py b/ae_size.py
index 7bef9f5..7183937 100755
--- a/ae_size.py
+++ b/ae_size.py
@@ -18,20 +18,26 @@ def minimal_input_size(w, layer_specs):
 
 ######################################################################
 
-layer_specs = [ (11, 5), (5, 2), (3, 2), (3, 2) ]
+# Dummy test
 
-layers = []
-for l in layer_specs:
-    layers.append(nn.Conv2d(1, 1, l[0], l[1]))
+if __name__ == "__main__":
 
-for l in reversed(layer_specs):
-    layers.append(nn.ConvTranspose2d(1, 1, l[0], l[1]))
+    layer_specs = [ (11, 5), (5, 2), (3, 2), (3, 2) ]
 
-m = nn.Sequential(*layers)
+    layers = []
+    for l in layer_specs:
+        layers.append(nn.Conv2d(1, 1, l[0], l[1]))
 
-h = minimal_input_size(240, layer_specs)
-w = minimal_input_size(320, layer_specs)
+    for l in reversed(layer_specs):
+        layers.append(nn.ConvTranspose2d(1, 1, l[0], l[1]))
 
-x = Tensor(1, 1, h, w).normal_()
+    m = nn.Sequential(*layers)
 
-print(x.size(), m(x).size())
+    h = minimal_input_size(240, layer_specs)
+    w = minimal_input_size(320, layer_specs)
+
+    x = Tensor(1, 1, h, w).normal_()
+
+    print(x.size(), m(x).size())
+
+######################################################################