gradient still not implemented fot there is an undefined gradient

theano/tensor/extra_ops.py

@@ -8,6 +8,7 @@ tensor = basic
 from theano.gradient import DisconnectedType
 
 
+
 class CumsumOp(theano.Op):
     # See function cumsum for docstring
     def __init__(self, axis=None):
@@ -730,7 +731,7 @@ def fill_diagonal(a, val):
 
 # Offset version of fill_diagonal
 class FillDiagonalOffset(gof.Op):
-    # See function fill_diagonal for docstring
+    # See function fill_diagonal_offset for docstring
     def __eq__(self, other):
         return type(self) == type(other)
 
@@ -778,7 +779,7 @@ class FillDiagonalOffset(gof.Op):
             start = offset
             num_of_step = min( min(width,height), width - offset) 
         else:
-            start = - offset * a.shape[0]
+            start = - offset * a.shape[1]
             num_of_step = min( min(width,height), height + offset)
         step = a.shape[1] + 1
         end = start + step * num_of_step
@@ -797,14 +798,18 @@ class FillDiagonalOffset(gof.Op):
         grad = cost_grad[0]
         if (a.dtype.startswith('complex')):
             return [None, None]
-        elif a.ndim > 2:
-            raise NotImplementedError('%s: gradient is currently implemented'
-                            ' for matrices only' % self.__class__.__name__)
-        wr_a = fill_diagonal_offset(grad, 0, offset)  # valid for any number of dimensions
-        # diag is only valid for matrices
+
+        # only valid for matrices        
+        wr_a = fill_diagonal_offset(grad, 0, offset)  
         import theano.sandbox.linalg
         wr_val = theano.sandbox.linalg.ops.diag(grad).sum()
-        return [wr_a, wr_val]
+        wr_offset = axis_grad = theano.gradient.grad_undefined(
+            self, 2, offset,
+            "offset is not defined for non-integer offset so"
+            " fill_diagonal_offset(a,val,offset+eps) is undefined")
+
+        return [wr_a, wr_val,wr_offset]
+
 fill_diagonal_offset_ = FillDiagonalOffset()
 
 

theano/tensor/tests/test_extra_ops.py

@@ -479,32 +479,46 @@ class TestFillDiagonalOffset(utt.InferShapeTester):
         y = tensor.scalar()
         z = tensor.scalar()
 
-        f = function([x, y, z], fill_diagonal(x, y, z))
+        test_offset = numpy.array(numpy.random.randint(-5,5),
+            dtype = config.floatX)
+
+        f = function([x, y, z], fill_diagonal_offset(x, y, z))
         for shp in [(8, 8), (5, 8), (8, 5)]:
             a = numpy.random.rand(*shp).astype(config.floatX)
             val = numpy.cast[config.floatX](numpy.random.rand())
-            out = f(a, val, offset)
+            out = f(a, val, test_offset)
             # We can't use numpy.fill_diagonal as it is bugged.
-            assert numpy.allclose(numpy.diag(out, offset), val)
-            assert (out == val).sum() == min(a.shape)
+            #pdb.set_trace()
+            assert numpy.allclose(numpy.diag(out, test_offset), val)
+            #pdb.set_trace()
+            if test_offset >= 0:
+                assert (out == val).sum() == min( min(a.shape), 
+                                        a.shape[1]-test_offset )
+            else:
+                assert (out == val).sum() == min( min(a.shape), 
+                                        a.shape[0]+test_offset )
 
     def test_gradient(self):
+        test_offset = numpy.array(numpy.random.randint(-5,5),
+                        dtype = config.floatX)
         utt.verify_grad(fill_diagonal_offset, [numpy.random.rand(5, 8),
-                                        numpy.random.rand()],
+                                        numpy.random.rand(),
+                                        test_offset],
                         n_tests=1, rng=TestFillDiagonalOffset.rng)
         utt.verify_grad(fill_diagonal_offset, [numpy.random.rand(8, 5),
-                                        numpy.random.rand()],
+                                        numpy.random.rand(),
+                                        test_offset],
                         n_tests=1, rng=TestFillDiagonalOffset.rng)
 
     def test_infer_shape(self):
         x = tensor.dmatrix()
         y = tensor.dscalar()
         z = tensor.dscalar()
+        test_offset = numpy.array(numpy.random.randint(-5,5),
+                        dtype = config.floatX)
         self._compile_and_check([x, y, z], [self.op(x, y, z)],
                                 [numpy.random.rand(8, 5),
                                  numpy.random.rand(),
-                                 numpy.random.randint(0,5)],
+                                 test_offset],
                                 self.op_class)
 
-if __name__ == '__main__':
-    unittest.main()
\ No newline at end of file

theano/tensor/tests/test_sort.py

@@ -143,3 +143,5 @@ def test_argsort():
     gv = f(m_val)
     gt = np.argsort(m_val, None)
     assert np.allclose(gv, gt)
+
+