--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/datasets/dataset.py	Thu Feb 25 18:40:01 2010 -0500
@@ -0,0 +1,46 @@
+from dsetiter import DataIterator
+
+class DataSet(object):
+    def test(self, batchsize, bufsize=None): 
+        r"""
+        Returns an iterator over the test examples.
+
+        Parameters
+          batchsize (int) -- the size of the minibatches, 0 means
+                             return the whole set at once.
+          bufsize (int, optional) -- the size of the in-memory buffer,
+                                     0 to disable.
+        """
+        return self._return_it(batchsize, bufsize, self._test)
+
+    def train(self, batchsize, bufsize=None):
+        r"""
+        Returns an iterator over the training examples.
+
+        Parameters
+          batchsize (int) -- the size of the minibatches, 0 means
+                             return the whole set at once.
+          bufsize (int, optional) -- the size of the in-memory buffer,
+                                     0 to disable.
+        """
+        return self._return_it(batchsize, bufsize, self._train)
+
+    def valid(self, batchsize, bufsize=None):
+        r"""
+        Returns an iterator over the validation examples.
+
+        Parameters
+          batchsize (int) -- the size of the minibatches, 0 means
+                             return the whole set at once.
+          bufsize (int, optional) -- the size of the in-memory buffer,
+                                     0 to disable.
+        """
+        return self._return_it(batchsize, bufsize, self._valid)
+
+    def _return_it(batchsize, bufsize, data):
+        r"""
+        Must return an iterator over the specified dataset (`data`).
+
+        Implement this in subclassses.
+        """
+        raise NotImplemented