merge

theano/sandbox/neighbours.py

@@ -46,6 +46,9 @@ class Images2Neibs(Op):
 
         return Apply(self, [ten4, neib_shape,neib_step], [T.matrix(dtype=ten4.type.dtype)])
 
+    def grad(self, (x, neib_shape, neib_step), (gz,)):
+        return [neibs2images(gz, neib_shape, x.shape), None, None]
+
     def c_code_cache_version(self):
         return (3,)
                 
@@ -211,36 +214,16 @@ class Images2Neibs(Op):
 def images2neibs(ten4, neib_shape, neib_step=None, mode='valid'):
     return Images2Neibs(mode)(ten4, neib_shape, neib_step)
 
-def neibs2images(neibs, neib_shape, original_shape, neib_step=None, mode='valid'):
+def neibs2images(neibs, neib_shape, original_shape):
     """
-    Inverse of images2neib. Don't implement neib_step and mode.
-    
-    :type neibs: Theano variable
-    :param neibs: matrix like the one obtained by images2neib
-
-    :type neib_shape: Theano variable
-    :param neib_shape: neib_shape that was used in images2neib
-
-    :type original_shape: Theano variable
-    :param original_shape: original shape of the 4d tensor given to images2neib.
-
-    :type neib_step: Theano variable or None
-    :param neib_step: neib_step that was used in images2neib Implement only None.
-                      None is non overlapping patches and not-adjacent patches.
+    Inverse of images2neib.
     
-    :type mode: str
-    :param mode: The mode that was used in images2neib. Implement only valid.
+    neibs : matrix like the one obtained by images2neib
+    neib_shape : neib_shape that was used in images2neib
+    original_shape : original shape of the 4d tensor given to images2neib
     
     Return a 4d tensor of shape `original_shape`.
     """
-    # TODO: handle the case where patches either overlap
-    # TODO: handle the case where patches are not directly adjacent
-    # TODO: at least separate these cases so that the following code does not incorrectly
-    # handle them by accident.
-    if neib_step != None:
-        raise NotImplementedError('neibs2images do not implement overlapping patches or non-adjacent patches.')
-    if mode != 'valid':
-        raise NotImplementedError('neibs2images do not implement the mode %s. It currently only implement `valid`.'%mode)
     neibs = T.as_tensor_variable(neibs)
     neib_shape = T.as_tensor_variable(neib_shape)
     original_shape = T.as_tensor_variable(original_shape)

theano/sandbox/test_neighbours.py

@@ -328,8 +328,56 @@ def speed_neibs_wrap_centered():
     for i in range(1000):
         f()
         
+def test_neibs_grad():
+    shape = (2,3,4,4)
+    images = T.shared(numpy.arange(numpy.prod(shape), dtype='float32').reshape(shape))
+
+    cost = T.sum(T.sqr(images2neibs(images, (2,2))), axis=[0,1])
+
+    grad = T.grad(cost, images)
+
+    f = theano.function([], [cost, grad], mode=mode_without_gpu)
+
+    got = f()
+
+    should_get = [numpy.asarray(290320.0, dtype=numpy.float32),
+        numpy.asarray([[[[   0.,    2.,    4.,    6.],
+         [   8.,   10.,   12.,   14.],
+         [  16.,   18.,   20.,   22.],
+         [  24.,   26.,   28.,   30.]],
+
+        [[  32.,   34.,   36.,   38.],
+         [  40.,   42.,   44.,   46.],
+         [  48.,   50.,   52.,   54.],
+         [  56.,   58.,   60.,   62.]],
+
+        [[  64.,   66.,   68.,   70.],
+         [  72.,   74.,   76.,   78.],
+         [  80.,   82.,   84.,   86.],
+         [  88.,   90.,   92.,   94.]]],
+
+
+       [[[  96.,   98.,  100.,  102.],
+         [ 104.,  106.,  108.,  110.],
+         [ 112.,  114.,  116.,  118.],
+         [ 120.,  122.,  124.,  126.]],
+
+        [[ 128.,  130.,  132.,  134.],
+         [ 136.,  138.,  140.,  142.],
+         [ 144.,  146.,  148.,  150.],
+         [ 152.,  154.,  156.,  158.]],
+
+        [[ 160.,  162.,  164.,  166.],
+         [ 168.,  170.,  172.,  174.],
+         [ 176.,  178.,  180.,  182.],
+         [ 184.,  186.,  188.,  190.]]]], dtype=numpy.float32)]
+
+    assert numpy.allclose(got[0], should_get[0])
+    assert numpy.allclose(got[1], should_get[1])
 
 
 if __name__ == '__main__':
-    test_neibs_gpu()
-    test_neibs()
+    #test_neibs_gpu()
+    #test_neibs()
+    test_neibs_grad()
+