--- a/pylearn/datasets/tzanetakis.py	Mon Mar 30 19:51:13 2009 -0400
+++ b/pylearn/datasets/tzanetakis.py	Wed Apr 01 19:48:32 2009 -0400
@@ -61,8 +61,13 @@
 import theano
 
 class TzanetakisExample(theano.Op):
+    """Return the i'th file, label pair from the Tzanetakis dataset."""
     @staticmethod
     def read_tzanetakis_file():
+        """Read the tzanetakis dataset file 
+        :rtype: (list, list)
+        :returns: paths, labels
+        """
         tracklist = open(data_root() + '/tzanetakis/tracklist.txt')
         path = []
         label = []
@@ -77,24 +82,45 @@
                 raise
         assert len(path) == 1000
         return path, label
+
+    nclasses = 10
+
+    class_idx_dict = dict(blues=numpy.asarray(0),
+            classical=1,
+            country=2,
+            disco=3,
+            hiphop=4,
+            jazz=5,
+            metal=6,
+            pop=7,
+            reggae=8,
+            rock=9)
             
     def __init__(self):
         self.path, self.label = self.read_tzanetakis_file()
+        self.class_idx_dict = {}
+        classes = ('blues classical country disco hiphop jazz metal pop reggae rock').split()
+        for i, c in enumerate(classes):
+            self.class_idx_dict[c] = numpy.asarray(i, dtype='int64')
 
     def __len__(self):
         return len(self.path)
 
     def make_node(self, idx):
+        idx_ = theano.tensor.as_tensor_variable(idx)
+        if idx_.type not in theano.tensor.int_types:
+            raise TypeError(idx)
         return theano.Apply(self, 
-                [theano.tensor.as_tensor_variable(idx)],
-                [theano.generic(), theano.generic()])
+                [idx_],
+                [theano.generic('tzanetakis_path'), 
+                    theano.tensor.lscalar('tzanetakis_label')])
 
-    def perform(self, node, (idx,), outputs):
-        assert len(outputs) == 2
-        outputs[0][0] = self.path[idx]
-        outputs[1][0] = self.label[idx]
+    def perform(self, node, (idx,), (path, label)):
+        path[0] = self.path[idx]
+        label[0] = self.class_idx_dict[self.label[idx]]
 
     def grad(self, inputs, g_output):
         return [None for i in inputs]
+
 tzanetakis_example = TzanetakisExample()
 

--- a/pylearn/io/wavread.py	Mon Mar 30 19:51:13 2009 -0400
+++ b/pylearn/io/wavread.py	Wed Apr 01 19:48:32 2009 -0400
@@ -47,7 +47,7 @@
         else:
             raise NotImplementedError()
 
-        sr[0] = w.getframerate()
+        sr[0] = numpy.asarray(w.getframerate(),dtype='float64')
 
     def grad(self, inputs, g_output):
         return [None for i in inputs]