# HG changeset patch
# User James Bergstra <bergstrj@iro.umontreal.ca>
# Date 1225465705 14400
# Node ID a4d34dad3083faec8f760cf5fc5a9bf6c7290a6b
# Parent  6103dc5d2a0d8c289301c005b1ed198654a95261# Parent  58810b63292bfad5cf4e3d3170dec4ed976a7764
merged

diff -r 58810b63292b -r a4d34dad3083 algorithms/daa.py
--- a/algorithms/daa.py	Thu Oct 30 23:27:27 2008 -0400
+++ b/algorithms/daa.py	Fri Oct 31 11:08:25 2008 -0400
@@ -7,12 +7,34 @@
 from pylearn import cost as cost
 
 class DenoisingAA(T.RModule):
+    """De-noising Auto-encoder
+
+    WRITEME
+
+    Abstract base class. Requires subclass with functions:
+    
+    - build_corrupted_input()
+
+    Introductory article about this model WRITEME.
+
+
+    """
 
     def __init__(self, input = None, regularize = True, tie_weights = True,
             activation_function=NN.sigmoid, reconstruction_cost_function=cost.cross_entropy):
         """
-        @param reconstruction_cost: Should return one cost per example (row)
-        @todo: Default noise level for all daa levels
+        :param input: WRITEME
+
+        :param regularize: WRITEME
+
+        :param tie_weights: WRITEME
+
+        :param activation_function: WRITEME
+
+        :param reconstruction_cost: Should return one cost per example (row)
+
+        :todo: Default noise level for all daa levels
+
         """
         super(DenoisingAA, self).__init__()