fix test

Author: kozlov721

luxonis_train/nodes/backbones/dinov3/dinov3.py

@@ -206,6 +206,7 @@ def _get_backbone(
             model=model_name,
             weights=weights,
             source="github",
+            trust_repo=True,  # type: ignore
             **kwargs,
         )
 

luxonis_train/nodes/backbones/efficientnet.py

@@ -43,6 +43,7 @@ class GenEfficientNet(nn.Module):
                 "rwightman/gen-efficientnet-pytorch",
                 "efficientnet_lite0",
                 pretrained=weights == "download",
+                trust_repo=True,  # type: ignore
             ),
         )
         self.out_indices = out_indices or [0, 1, 2, 4, 6]

luxonis_train/utils/dataset_metadata.py

@@ -103,7 +103,8 @@ def n_classes(self, task_name: str | None = None) -> int:
         if task_name is not None:
             if task_name not in self._classes:
                 raise ValueError(
-                    f"Task '{task_name}' is not present in the dataset."
+                    f"Task '{task_name}' is not present in the dataset. "
+                    f"Available tasks: {self.task_names}"
                 )
             return len(self._classes[task_name])
         n_classes = len(next(iter(self._classes.values())))
@@ -155,7 +156,8 @@ def classes(self, task_name: str | None = None) -> bidict[str, int]:
         if task_name is not None:
             if task_name not in self._classes:
                 raise ValueError(
-                    f"Task '{task_name}' is not present in the dataset."
+                    f"Task '{task_name}' is not present in the dataset. "
+                    f"Available tasks: {self.task_names}"
                 )
             return bidict(self._classes[task_name])
         classes = next(iter(self._classes.values()))

tests/conftest.py

@@ -406,7 +406,7 @@ def opts(save_dir: Path, image_size: tuple[int, int]) -> Params:
         "tracker.save_directory": str(save_dir),
         "trainer.preprocessing.train_image_size": image_size,
         "exporter.aimet": {
-            "active": True,
+            "active": False,
             "epochs": 1,
             "fold_batch_norms": True,
             "batch_norm_reestimation": True,

tests/integration/test_callbacks.py

@@ -56,6 +56,8 @@ def test_callbacks(coco_dataset: LuxonisDataset, opts: Params, save_dir: Path):
         "exporter.scale_values": [0.5, 0.5, 0.5],
         "exporter.mean_values": [0.5, 0.5, 0.5],
         "exporter.blobconverter.active": True,
+        # AIMET fails when determinism is enabled
+        "exporter.aimet.active": False,
         "loader.params.dataset_name": coco_dataset.identifier,
     }
     model = LuxonisModel(config_file, opts, debug_mode=True)

tests/integration/test_combinations.py

@@ -143,7 +143,9 @@ def test_combinations(
     subtests: SubTests,
 ):
     config = get_config(backbone, dinov3_weights)
-    opts |= {"loader.params.dataset_name": parking_lot_dataset.identifier}
+    opts |= {
+        "loader.params.dataset_name": parking_lot_dataset.identifier,
+    }
     model = LuxonisModel(config, opts)
 
     with subtests.test("train"):

tests/integration/test_custom_model.py

@@ -30,7 +30,7 @@ def input_shapes(self):
             "pointcloud": torch.Size([self.n_points, 3]),
         }
 
-    def get(self, _: int) -> LuxonisLoaderTorchOutput:
+    def __getitem__(self, _: int) -> LuxonisLoaderTorchOutput:
         left = torch.rand(3, self.height, self.width, dtype=torch.float32)
         right = torch.rand(3, self.height, self.width, dtype=torch.float32)
         disparity = torch.rand(1, self.height, self.width, dtype=torch.float32)

tests/integration/test_predefined_models.py

@@ -48,7 +48,9 @@ def test_predefined_models(
     tmp_path = tmp_path / config_name
     tmp_path.mkdir()
 
-    model = LuxonisModel(config_file, opts | extra_opts)
+    model = LuxonisModel(
+        config_file, opts | extra_opts | {"exporter.aimet.active": True}
+    )
 
     with subtests.test("train"):
         model.train()