--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sandbox/simple_autoassociator/graph.py	Tue Jul 08 18:46:26 2008 -0400
@@ -0,0 +1,26 @@
+"""
+Theano graph for a simple autoassociator.
+@todo: Make nearly everything private.
+"""
+
+from pylearn.nnet_ops import sigmoid, binary_crossentropy
+from theano import tensor as t
+from theano.tensor import dot
+x           = t.dvector()
+w1          = t.dmatrix()
+b1          = t.dvector()
+w2          = t.dmatrix()
+b2          = t.dvector()
+h           = sigmoid(dot(x, w1) + b1)
+y           = sigmoid(dot(h, w2) + b2)
+
+loss_unsummed = binary_crossentropy(y, x)
+loss = t.sum(loss_unsummed)
+
+(gw1, gb1, gw2, gb2, gy) = t.grad(loss, [w1, b1, w2, b2, y])
+
+import theano.compile
+
+inputs  = [x, w1, b1, w2, b2]
+outputs = [y, h, loss, loss_unsummed, gw1, gb1, gw2, gb2, gy]
+trainfn = theano.compile.function(inputs, outputs)