updated convOp grad to use nicer dimshuffle notation

theano/sandbox/conv.py

@@ -281,8 +281,8 @@ class ConvOp(Op):
         ####### Determine gradient on kernels ########
         assert inputs.ndim==4 and kerns.ndim==4
 
-        newin = tensor.DimShuffle(inputs.broadcastable, (1,0,2,3))(inputs)
-        newgz = tensor.DimShuffle(gz.broadcastable, (1,0,2,3))(gz)
+        newin = inputs.dimshuffle((1,0,2,3))
+        newgz = gz.dimshuffle((1,0,2,3))
     
         if self.out_mode == 'valid':
             (img, filters) = (newin, newgz)
@@ -336,12 +336,12 @@ class ConvOp(Op):
         assert (dw.owner.op.outshp==self.kshp).all()
         if self.out_mode == 'valid':
             # before DimShuffle, dw is of shape visdim x nkern x kshp[0] x kshp[1]
-            dw = tensor.DimShuffle(dw.broadcastable, (1,0,2,3))(dw)
+            dw = dw.dimshuffle((1,0,2,3))
             dw = dw[:,:,::-1,::-1]
 
         ####### Determine gradient on inputs ########
         mode = 'valid' if self.out_mode == 'full' else 'full'
-        filters = tensor.DimShuffle(kerns.broadcastable, (1,0,2,3))(kerns)
+        filters = kerns.dimshuffle((1,0,2,3))
         filters = filters[:,:,::-1,::-1]
         nkern = self.imshp[0]
         imshp = (self.nkern, self.outshp[0], self.outshp[1])