merge

theano/sparse/basic.py

@@ -11,6 +11,7 @@ import numpy, theano
 import scipy.sparse
 from theano.printing import Print
 
+
 from theano import gof
 from theano import tensor
 from theano import compile
@@ -532,6 +533,7 @@ class Transpose(gof.op.Op):
     def perform(self, node, (x, ), (out, )):
         assert _is_sparse(x)
         out[0] = x.transpose()
+
     def grad(self, (x,), (gz,)):
         assert _is_sparse_variable(x) and _is_sparse_variable(gz)
         return transpose(gz),
@@ -738,7 +740,7 @@ class StructuredDot(gof.Op):
     def __hash__(self):
         return hash(type(self))
     def make_node(self, a, b):
-        if type(a) is not SparseVariable and type(a) is not SparseConstant:
+        if not _is_sparse_variable(a):
             raise TypeError('First argument must be of type SparseVariable or SparseConstant');
         dtype_out = scalar.upcast(a.type.dtype, b.type.dtype)
         if b.type.ndim != 2:
@@ -792,7 +794,6 @@ def structured_dot(x, y):
 
     x_is_sparse_variable = _is_sparse_variable(x)
     y_is_sparse_variable = _is_sparse_variable(y)
-
     if not x_is_sparse_variable and not y_is_sparse_variable:
         raise TypeError('structured_dot requires at least one sparse argument')