some modification

theano/tensor/nnet/neighbours.py

@@ -85,9 +85,6 @@ class Images2Neibs(Op):
         assert neib_shape.ndim == 1
         assert neib_step.ndim == 1
 
-        self.neib_shape = neib_shape
-        self.neib_step = neib_step
-        
         return Apply(self, [ten4, neib_shape, neib_step],
                      [T.matrix(dtype=ten4.type.dtype)])
 
@@ -219,8 +216,8 @@ class Images2Neibs(Op):
                 return (a // b) + 1
             else:
                 return a // b
-        c, d = self.neib_shape
-        step_x, step_y = self.neib_step
+        c, d = node.inputs[1]
+        step_x, step_y = node.inputs[2]
         if self.mode == 'wrap_centered':
             grid_c = CEIL_INTDIV(in_shape[2], step_x)
             grid_d = CEIL_INTDIV(in_shape[3], step_y)

theano/tensor/nnet/tests/test_neighbours.py

@@ -377,9 +377,37 @@ class T_Images2Neibs(unittest_tools.InferShapeTester):
                                     [images],
                                     Images2Neibs
                                     )
+        f = self._compile_and_check([x],
+                                    [images2neibs(
+                                        x, neib_shape=(2,3),
+                                        mode='valid')],
+                                    [images],
+                                    Images2Neibs
+                                    )
+        shape = (100, 40, 5, 5)
+        images = numpy.ones(shape).astype('float32')
+        x = T.ftensor4()
+        f = self._compile_and_check([x],
+                                    [images2neibs(
+                                        x, neib_shape=(2,2),
+                                        mode='ignore_borders')],
+                                    [images],
+                                    Images2Neibs
+                                    )
         shape = (100, 40, 5, 5)
         images = numpy.ones(shape).astype('float32')
         x = T.ftensor4()
+        f = self._compile_and_check([x],
+                                    [images2neibs(
+                                        x, neib_shape=(2,3),
+                                        mode='ignore_borders')],
+                                    [images],
+                                    Images2Neibs
+                                    )
+
+        shape = (100, 40, 6, 6)
+        images = numpy.ones(shape).astype('float32')
+        x = T.ftensor4()
         f = self._compile_and_check([x],
                                     [images2neibs(
                                         x, neib_shape=(2,2),
@@ -397,6 +425,7 @@ class T_Images2Neibs(unittest_tools.InferShapeTester):
                                     [images],
                                     Images2Neibs
                                     )
+        
 
 if __name__ == '__main__':
     unittest.main()