✅Enhanced coverage

.coveragerc

@@ -1,4 +1,3 @@
 [report]
-exclude_lines = 
-    pragma: no cover
+exclude_also =
     if TYPE_CHECKING:

core/learn/callbacks/defaults.py

@@ -104,7 +104,7 @@ def before_loop_with_loaders(
             return None
         if valid_loader is not None:
             loader = valid_loader
-        else:
+        else:  # pragma: no cover
             if (
                 console.ask(
                     "no validation loader found, do you want to calculate resumed-metrics from the training loader?",

core/learn/pipeline/blocks/basic.py

@@ -978,7 +978,7 @@ def save_extra(self, folder: TPath) -> None:
         accelerator = self.build_trainer.trainer.accelerator
         if accelerator is not None:
             scaler = accelerator.scaler
-            if scaler is not None:
+            if scaler is not None:  # pragma: no cover
                 torch.save(scaler.state_dict(), os.path.join(folder, self.scaler_file))
         state = self.build_trainer.trainer.state
         if state is not None:
@@ -1004,7 +1004,7 @@ def load_from(self, folder: TPath) -> None:
             if k_sch is not None:
                 k_sch.load_state_dict(states)
         accelerator = self.build_trainer.trainer.accelerator
-        if accelerator is not None:
+        if accelerator is not None:  # pragma: no cover
             scaler_path = folder / self.scaler_file
             if scaler_path.is_file():
                 scaler = accelerator.scaler

tests/test_learn/test_losses.py

@@ -32,6 +32,11 @@ def test_corr_loss(self) -> None:
         torch.testing.assert_close(corr, gt_corr)
 
     def test_multi_loss(self) -> None:
+        @cflearn.register_loss("foo")
+        class _(cflearn.ILoss):
+            def forward(self, forward_results, batch, state=None) -> None:
+                return None
+
         x = torch.randn(13, 1)
         y = torch.randn(13, 1)
         mse = get_loss("mae", x, y)
@@ -44,6 +49,7 @@ def test_multi_loss(self) -> None:
             losses=[
                 {"name": "mse", "weight": 0.17},
                 {"name": "corr", "weight": 0.19},
+                {"name": "foo", "weight": 123.456},
             ],
         )[cflearn.LOSS_KEY]
         multi = get_loss(

tests/test_toolkit/test_misc.py

@@ -820,9 +820,12 @@ def test_format_float(self):
 
     def test_track(self):
         for _ in track(range(2)):
-            time.sleep(1.01)
+            time.sleep(1.1)
         for _ in track(range(3), leave=False):
             pass
+        for _ in track(range(3), leave=False):
+            for _ in track(range(3), leave=False):
+                pass
         nums = []
         for _ in track(range(3), update_callback=lambda *_: nums.append(1)):
             pass