documentation of the update part of partial function evaluation

theano/compile/function_module.py

@@ -735,9 +735,13 @@ class Function(object):
         kwargs : dict
             The function inputs can be passed as keyword argument. For this, use
             the name of the input or the input instance as the key.
+
             Keyword argument ``output_subset`` is a list of either indices of the
             function's outputs or the keys belonging to the `output_keys` dict
-            and represent outputs that are requested to be calculated.
+            and represent outputs that are requested to be calculated. Regardless
+            of the presence of ``output_subset``, the updates are always calculated
+            and processed. To disable the updates, you should use the ``copy``
+            method with ``delete_updates=False``.
 
         Returns
         -------

theano/gof/tests/test_vm.py

@@ -212,15 +212,19 @@ def test_partial_function():
     check_partial_function('cvm')
 
 
-# TODO: implement output_keys with CVM
-def test_partial_function_output_keys():
+def test_partial_function_with_output_keys():
+
+    def check_partial_function_output_keys(linker_name):
         x = tensor.scalar('input')
         y = 3 * x
         f = theano.function([x], {'a': y * 5, 'b': y - 7}, mode=Mode(
-        optimizer=None, linker=vm.VM_Linker(allow_partial_eval=True)))
+            optimizer=None, linker=linker_name))
 
         assert f(5, output_subset=['a'])['a'] == f(5)['a']
 
+    check_partial_function_output_keys(vm.VM_Linker(allow_partial_eval=True))
+    check_partial_function_output_keys('cvm')
+
 
 def test_partial_function_with_updates():