import fix in sparse sandbox.

theano/sparse/sandbox/truedot.py

+import unittest
+
+import numpy
+
+from theano import gof, tensor,compile
+
+from theano.sparse.tests.test_basic import eval_outputs
+from theano.sparse.basic import _is_sparse_variable, _is_dense_variable, as_sparse_variable, _is_sparse, _mtypes, _mtype_to_str
+from theano.sparse import SparseType, dense_from_sparse, transpose
 
 ###############
 #
@@ -43,7 +52,7 @@ class TrueDot(gof.op.Op):
             raise NotImplementedError()
 
         inputs = [x, y]    # Need to convert? e.g. assparse
-        outputs = [Sparse(dtype = x.type.dtype, format = myformat).make_variable()]
+        outputs = [SparseType(dtype = x.type.dtype, format = myformat).make_variable()]
         return gof.Apply(self, inputs, outputs)
     def perform(self, node, inp, out_):
         """
@@ -194,7 +203,7 @@ class test_true_dot(unittest.TestCase):
     def test_graph_bprop0(self):
         for mtype in _mtypes:
             x = tensor.matrix('x') #TensorType('float64', broadcastable=[False,False], name='x')
-            w = Sparse(dtype = 'float64', format = _mtype_to_str[mtype]).make_variable()
+            w = SparseType(dtype = 'float64', format = _mtype_to_str[mtype]).make_variable()
             xw = dense_from_sparse(true_dot(w, x))
             y = dense_from_sparse(true_dot(w.T, xw))
             diff = x-y
@@ -221,7 +230,7 @@ class test_true_dot(unittest.TestCase):
             xorig = numpy.random.rand(3,2)
             for mtype in _mtypes:
                 x = tensor.matrix('x')
-                w = Sparse(dtype = 'float64', format = _mtype_to_str[mtype]).make_variable()
+                w = SparseType(dtype = 'float64', format = _mtype_to_str[mtype]).make_variable()
                 xw = dense_from_sparse(true_dot(w, x))
                 y = dense_from_sparse(true_dot(w.T, xw))
                 diff = x-y