Fix a bug with custom attribute name clashes

CHANGES.md

@@ -16,6 +16,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Fixed
 
 - Make skorch compatible with sklearn 0.22
+- Fixed a bug that could occur when a new "settable" (via `set_params`) attribute was added to `NeuralNet` whose name starts the same as an existing attribute's name
 
 ## [0.7.0] - 2019-11-29
 

skorch/net.py

@@ -1334,7 +1334,10 @@ def _check_kwargs(self, kwargs):
         for key in kwargs:
             if key.endswith('_'):
                 continue
-            for prefix in self.prefixes_:
+
+            # see https://github.com/skorch-dev/skorch/pull/590 for
+            # why this must be sorted
+            for prefix in sorted(self.prefixes_, key=lambda s: (-len(s), s)):
                 if key.startswith(prefix):
                     if not key.startswith(prefix + '__'):
                         missing_dunder_kwargs.append((prefix, key))

skorch/tests/test_net.py

@@ -169,7 +169,7 @@ def test_net_init_one_unknown_argument(self, net_cls, module_cls):
                     "should deal with the new arguments explicitely.")
         assert e.value.args[0] == expected
 
-    def test_net_init_two_unknown_argument(self, net_cls, module_cls):
+    def test_net_init_two_unknown_arguments(self, net_cls, module_cls):
         with pytest.raises(TypeError) as e:
             net_cls(module_cls, lr=0.1, mxa_epochs=5,
                     warm_start=False, bathc_size=20)
@@ -231,6 +231,27 @@ def test_net_init_missing_dunder_and_unknown(
                     "did you mean iterator_train__shuffle?")
         assert e.value.args[0] == expected
 
+    def test_net_with_new_attribute_with_name_clash(
+            self, net_cls, module_cls):
+        # This covers a bug that existed when a new "settable"
+        # argument was added whose name starts the same as the name
+        # for an existing argument
+        class MyNet(net_cls):
+            # add "optimizer_2" as a valid prefix so that it works
+            # with set_params
+            prefixes_ = net_cls.prefixes_[:] + ['optimizer_2']
+
+            def __init__(self, *args, **kwargs):
+                super().__init__(*args, **kwargs)
+                self.optimizer_2 = torch.optim.SGD
+
+        # the following line used to raise this error: "TypeError: Got
+        # an unexpected argument optimizer_2__lr, did you mean
+        # optimizer__2__lr?" because it was erronously assumed that
+        # "optimizer_2__lr" should be dispatched to "optimizer", not
+        # "optimizer_2".
+        MyNet(module_cls, optimizer_2__lr=0.123)  # should not raise
+
     def test_fit(self, net_fit):
         # fitting does not raise anything
         pass