X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;ds=sidebyside;f=denoising-ae-field.py;h=47e6ab4bdf54aa7a521a577bc074089cd3baf039;hb=aacb2bf640ba8342bb49f3a6c285d00fac523540;hp=8f748d11a3ff219922220b4ed9f14b3eb473a2e1;hpb=72e4bc5d20e153800f19a94e4bfd075adf30e3f3;p=pytorch.git

diff --git a/denoising-ae-field.py b/denoising-ae-field.py
index 8f748d1..47e6ab4 100755
--- a/denoising-ae-field.py
+++ b/denoising-ae-field.py
@@ -1,5 +1,10 @@
 #!/usr/bin/env python
 
+# Any copyright is dedicated to the Public Domain.
+# https://creativecommons.org/publicdomain/zero/1.0/
+
+# Written by Francois Fleuret <francois@fleuret.org>
+
 import math
 import matplotlib.pyplot as plt
 
@@ -61,7 +66,7 @@ def train_model(data):
 
 ######################################################################
 
-def save_image(data, data_name, model):
+def save_image(data_name, model, data):
     a = torch.linspace(-1.5, 1.5, 30)
     x = a.view( 1, -1, 1).expand(a.size(0), a.size(0), 1)
     y = a.view(-1,  1, 1).expand(a.size(0), a.size(0), 1)
@@ -104,4 +109,4 @@ for data_source in [ data_zigzag, data_spiral, data_penta ]:
     data, data_name = data_source(1000)
     data = data - data.mean(0)
     model = train_model(data)
-    save_image(data, data_name, model)
+    save_image(data_name, model, data)