test: add more tests

metaopt · XuehaiPan · Mar 7, 2023 · Mar 3, 2023 · Mar 3, 2023 · Mar 3, 2023
commit f3d86ee15ab807f10a6400497837bb2488573070
diff --git a/tests/.coveragerc b/tests/.coveragerc
@@ -6,3 +6,12 @@ omit =
     ../docs/*
     ../examples/*
     ../tutorials/*
+
+[report]
+exclude_lines =
+    pragma: no cover
+    raise NotImplementedError
+    class .*\bProtocol\):
+    @(abc\.)?abstractmethod
+    if __name__ == ('__main__'|"__main__"):
+    if TYPE_CHECKING:
diff --git a/tests/test_implicit.py b/tests/test_implicit.py
@@ -700,7 +700,7 @@ def __init__(self, x):
             self.x = x
 
         def objective(self):
-            return self.x
+            return self.x.mean()
 
         def solve(self):
             pass
@@ -722,6 +722,11 @@ def solve(self):
     with pytest.raises(RuntimeError, match='The module has no parameters.'):
         model.optimality()
 
+    model = EmptyParameters(torch.zeros(8))
+    model.register_parameter('y', torch.zeros(8, requires_grad=True))
+    with pytest.raises(RuntimeError, match='The module has no meta-parameters.'):
+        model.optimality()
+
     model = EmptyParameters(torch.zeros(8, requires_grad=True))
     model.register_parameter('y', torch.zeros(8, requires_grad=True))
     model.solve()
@@ -757,10 +762,7 @@ class MyModule1(torchopt.nn.ImplicitMetaGradientModule):
         def objective(self):
             return torch.tensor(0.0)
 
-    with pytest.raises(
-        TypeError,
-        match="Can't instantiate abstract class",
-    ):
+    with pytest.raises(TypeError, match="Can't instantiate abstract class"):
         MyModule1()
 
     with pytest.raises(
@@ -820,12 +822,12 @@ def solve(self):
 
     with pytest.raises(
         TypeError,
-        match=re.escape('method optimality() must not be a staticmethod.'),
+        match=re.escape('method objective(() must not be a staticmethod.'),
     ):
 
         class MyModule7(torchopt.nn.ImplicitMetaGradientModule):
             @staticmethod
-            def optimality():
+            def objective():
                 return ()
 
             def solve(self):

diff --git a/tests/test_zero_order.py b/tests/test_zero_order.py
@@ -155,18 +155,12 @@ class MyModule1(torchopt.nn.ZeroOrderGradientModule):
         def forward(self):
             return torch.tensor(0.0)
 
-    with pytest.raises(
-        TypeError,
-        match="Can't instantiate abstract class",
-    ):
+    with pytest.raises(TypeError, match="Can't instantiate abstract class"):
         MyModule1()
 
     class MyModule2(torchopt.nn.ZeroOrderGradientModule):
         def sample(self, sample_shape):
             return torch.tensor(0.0)
 
-    with pytest.raises(
-        TypeError,
-        match="Can't instantiate abstract class",
-    ):
+    with pytest.raises(TypeError, match="Can't instantiate abstract class"):
         MyModule2()
diff --git a/torchopt/base.py b/torchopt/base.py
@@ -38,7 +38,7 @@
 from typing import TYPE_CHECKING, Callable, NamedTuple, Protocol
 
 
-if TYPE_CHECKING:  # pragma: no cover
+if TYPE_CHECKING:
     from torchopt.typing import OptState, Params, Updates
 
 

diff --git a/torchopt/typing.py b/torchopt/typing.py
@@ -141,7 +141,7 @@ def sample(
     ) -> Union[Tensor, Sequence[Numeric]]:
         # pylint: disable-next=line-too-long
         """Generate a sample_shape shaped sample or sample_shape shaped batch of samples if the distribution parameters are batched."""
-        raise NotImplementedError  # pragma: no cover
+        raise NotImplementedError
 
 
 Samplable.register(Distribution)
diff --git a/torchopt/utils.py b/torchopt/utils.py
@@ -28,7 +28,7 @@
 from torchopt.typing import Device, ModuleTensorContainers, OptState, TensorContainer, TensorTree
 
 
-if TYPE_CHECKING:  # pragma: no cover
+if TYPE_CHECKING:
     from torchopt.optim.meta.base import MetaOptimizer