# HG changeset patch
# User Arnaud Bergeron <abergeron@gmail.com>
# Date 1271275603 14400
# Node ID 6143b23e2610d594f8cbcb0a2d5869a4fc010623
# Parent  69109e41983edb3334613818cc0c73749992052a
Name the important layers to be able to change them easily later.

diff -r 69109e41983e -r 6143b23e2610 deep/convolutional_dae/scdae.py
--- a/deep/convolutional_dae/scdae.py	Wed Apr 14 16:06:04 2010 -0400
+++ b/deep/convolutional_dae/scdae.py	Wed Apr 14 16:06:43 2010 -0400
@@ -31,7 +31,7 @@
                                          subsamplings, corruptions):
         layers.append(cdae(fsize, nfilt, old_nfilt, subs, corr, dtype))
         old_nfilt = nfilt
-    return LayerStack(layers)
+    return LayerStack(layers, name='scdae')
 
 def mlp(layer_sizes, dtype):
     layers = []
@@ -40,7 +40,7 @@
         layers.append(SimpleLayer(old_size, size, activation=nlins.tanh,
                                   dtype=dtype))
         old_size = size
-    return LayerStack(layers)
+    return LayerStack(layers, name='mlp')
 
 def scdae_net(in_size, filter_sizes, num_filts, subsamplings,
               corruptions, layer_sizes, out_size, dtype):
@@ -53,7 +53,8 @@
     rl2 = ReshapeLayer((None, outs))
     layer_sizes = [outs]+layer_sizes
     ls2 = mlp(layer_sizes, dtype)
-    lrl = SimpleLayer(layer_sizes[-1], out_size, activation=nlins.softmax)
+    lrl = SimpleLayer(layer_sizes[-1], out_size, activation=nlins.softmax, 
+                      name='output')
     return NNet([rl1, ls, rl2, ls2, lrl], error=errors.nll)
 
 def build_funcs(batch_size, img_size, filter_sizes, num_filters, subs,