--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sandbox/rbm/model.py	Tue Jul 08 20:14:21 2008 -0400
@@ -0,0 +1,66 @@
+"""
+The model for an autoassociator for sparse inputs, using Ronan Collobert + Jason
+Weston's sampling trick (2008).
+"""
+
+import parameters
+
+import globals
+from globals import LR
+
+import numpy
+from numpy import dot
+import random
+random.seed(globals.SEED)
+
+import pylearn.nnet_ops
+
+def sigmoid(v):
+#    if x < -30.0: return 0.0
+#    if x > 30.0: return 1.0 
+    return 1.0 / (1.0 + numpy.exp(-v))
+
+def sample(v):
+    assert len(v.shape) == 1
+    x = numpy.zeros(v.shape)
+    for i in range(v.shape[0]):
+        assert v[i] >= 0 and v[i] <= 1
+        if random.random() < v[i]: x[i] = 0
+        else: x[i] = 1
+    return x
+
+class Model:
+    def __init__(self):
+        self.parameters = parameters.Parameters(randomly_initialize=True)
+
+    def update(self, instance):
+        """
+        Update the L{Model} using one training instance.
+        @param instance: A dict from feature index to (non-zero) value.
+        @todo: Should assert that nonzero_indices and zero_indices
+        are correct (i.e. are truly nonzero/zero).
+        """
+        v0 = numpy.zeros(globals.INPUT_DIMENSION)
+        for idx in instance.keys():
+            v0[idx] = instance[idx]
+
+        q0 = sigmoid(self.parameters.b + dot(v0, self.parameters.w))
+        h0 = sample(q0)
+        p0 = sigmoid(self.parameters.c + dot(h0, self.parameters.w.T))
+        v1 = sample(p0)
+        q1 = sigmoid(self.parameters.b + dot(v1, self.parameters.w))
+        print
+        print "v[0]:", v0
+        print "Q(h[0][i] = 1 | v[0]):", q0
+        print "h[0]:", h0
+        print "P(v[1][j] = 1 | h[0]):", p0
+        print "v[1]:", v1
+        print "Q(h[1][i] = 1 | v[1]):", q1
+
+        print h0.shape
+        print v0.T.shape
+        print dot(h0, v0.T)
+        print dot(q1, v1.T)
+        self.parameters.w += LR * (dot(h0, v0.T) - dot(q1, v1.T))
+        self.parameters.b += LR * (h0 - q1)
+        self.parameters.c += LR * (v0 - v1)