Improve backend test robustness and imports

Refactor test startup and error handling for check_install and simplify a type-only import.

- dlclive/benchmark.py: replace the try/except tensorflow import under TYPE_CHECKING with a direct import (type ignored) to simplify typing logic.
- dlclive/check_install/check_install.py:
  - Defer importing export_modelzoo_model into run_pytorch_test to avoid importing heavy modules unless PyTorch test runs.
  - Move MODELS_FOLDER.mkdir to after temporary directory creation.
  - Add a --nodisplay flag and set default for --display to False so CLI can explicitly disable display.
  - Comment out resize parameters in test calls and remove an unnecessary model_dir.exists() assertion.
  - Wrap per-backend test runs in try/except, collect backend failures, allow other backends to continue, and raise an aggregated RuntimeError if all backend tests fail.

These changes improve robustness when some backends fail or are unavailable and reduce unnecessary imports during initial checks.

Author: C-Achard

dlclive/benchmark.py

@@ -31,10 +31,7 @@
 from dlclive.utils import decode_fourcc
 
 if TYPE_CHECKING:
-    try:
-        import tensorflow
-    except ImportError:
-        tensorflow = None
+    import tensorflow  # type: ignore
 
 
 def download_benchmarking_data(

dlclive/check_install/check_install.py

@@ -17,7 +17,6 @@
 from dlclive.utils import download_file
 from dlclive.benchmark import benchmark_videos
 from dlclive.engine import Engine
-from dlclive.modelzoo.pytorch_model_zoo_export import export_modelzoo_model
 from dlclive.utils import get_available_backends
 
 MODEL_NAME = "superanimal_quadruped"
@@ -32,10 +31,10 @@
 }
 TF_MODEL_DIR = TMP_DIR / "DLC_Dog_resnet_50_iteration-0_shuffle-0"
 
-MODELS_FOLDER.mkdir(parents=True, exist_ok=True)
-
 
 def run_pytorch_test(video_file: str, display: bool = False):
+    from dlclive.modelzoo.pytorch_model_zoo_export import export_modelzoo_model
+
     if Engine.PYTORCH not in get_available_backends():
         raise NotImplementedError(
             "PyTorch backend is not available. Please ensure PyTorch is installed to run the PyTorch test."
@@ -57,7 +56,7 @@ def run_pytorch_test(video_file: str, display: bool = False):
         model_type="pytorch",
         video_path=video_file,
         display=display,
-        resize=0.5,
+        # resize=0.5,
         pcutoff=0.25,
         pixels=1000,
     )
@@ -70,7 +69,6 @@ def run_tensorflow_test(video_file: str, display: bool = False):
         )
     model_dir = TF_MODEL_DIR
     model_dir.mkdir(parents=True, exist_ok=True)
-    assert model_dir.exists(), f"Model directory {model_dir} does not exist"
     if Path(model_dir / SNAPSHOT_NAME).exists():
         print("Model already downloaded, using cached version")
     else:
@@ -88,7 +86,7 @@ def run_tensorflow_test(video_file: str, display: bool = False):
         model_type="base",
         video_path=video_file,
         display=display,
-        resize=0.5,
+        # resize=0.5,
         pcutoff=0.25,
         pixels=1000,
     )
@@ -103,8 +101,16 @@ def main():
         parser.add_argument(
             "--display",
             action="store_true",
+            default=False,
             help="Run the test and display tracking",
         )
+        parser.add_argument(
+            "--nodisplay",
+            action="store_false",
+            dest="display",
+            help=argparse.SUPPRESS,
+        )
+
         args = parser.parse_args()
         display = args.display
 
@@ -115,6 +121,7 @@ def main():
         print("\nCreating temporary directory...\n")
         tmp_dir = TMP_DIR
         tmp_dir.mkdir(mode=0o775, exist_ok=True)
+        MODELS_FOLDER.mkdir(parents=True, exist_ok=True)
 
         video_file = str(tmp_dir / "dog_clip.avi")
 
@@ -132,19 +139,37 @@ def main():
 
         # assert these things exist so we can give informative error messages
         assert Path(video_file).exists(), f"Missing video file {video_file}"
+        backend_failures = {}
+        any_backend_succeeded = False
 
         for backend in get_available_backends():
-            if backend == Engine.PYTORCH:
-                print("\nRunning PyTorch test...\n")
-                run_pytorch_test(video_file, display=display)
-            elif backend == Engine.TENSORFLOW:
-                print("\nRunning TensorFlow test...\n")
-                run_tensorflow_test(video_file, display=display)
-            else:
+            try:
+                if backend == Engine.PYTORCH:
+                    print("\nRunning PyTorch test...\n")
+                    run_pytorch_test(video_file, display=display)
+                    any_backend_succeeded = True
+                elif backend == Engine.TENSORFLOW:
+                    print("\nRunning TensorFlow test...\n")
+                    run_tensorflow_test(video_file, display=display)
+                    any_backend_succeeded = True
+                else:
+                    warnings.warn(
+                        f"Unrecognized backend {backend}, skipping...", UserWarning
+                    )
+            except Exception as e:
+                backend_failures[backend] = e
                 warnings.warn(
-                    f"Unrecognized backend {backend}, skipping...", UserWarning
+                    f"Error while running test for backend {backend}: {e}. "
+                    "Continuing to test other available backends.",
+                    UserWarning,
                 )
 
+        if not any_backend_succeeded and backend_failures:
+            failure_messages = "; ".join(
+                f"{b}: {exc}" for b, exc in backend_failures.items()
+            )
+            raise RuntimeError(f"All backend tests failed. Details: {failure_messages}")
+
     finally:
         # deleting temporary files
         print("\n Deleting temporary files...\n")