Use the right dtype for the output allocation.

theano/sparse/basic.py

@@ -854,7 +854,8 @@ class CSMGrad(gof.op.Op):
             sp_dim = x_shape[0]
 
         g_row = numpy.zeros(sp_dim, dtype=g_data.dtype)
-        gout_data = numpy.zeros_like(x_data)
+        gout_data = numpy.zeros_like(x_data, dtype=node.outputs[0].dtype)
+
         for i in range(len(x_indptr) - 1):
             for j_ptr in range(g_indptr[i], g_indptr[i + 1]):
                 g_row[g_indices[j_ptr]] += g_data[j_ptr]