fix: Address PyTorch Model Loading Deprecation Warning (GH-30)

batdetect2/utils/detector_utils.py

@@ -85,6 +85,7 @@ def load_model(
     model_path: str = DEFAULT_MODEL_PATH,
     load_weights: bool = True,
     device: Optional[torch.device] = None,
+    weights_only: bool = True,
 ) -> Tuple[DetectionModel, ModelParameters]:
     """Load model from file.
 
@@ -105,7 +106,11 @@ def load_model(
     if not os.path.isfile(model_path):
         raise FileNotFoundError("Model file not found.")
 
-    net_params = torch.load(model_path, map_location=device)
+    net_params = torch.load(
+        model_path,
+        map_location=device,
+        weights_only=weights_only,
+    )
 
     params = net_params["params"]
 

tests/conftest.py

@@ -1,8 +1,31 @@
 from pathlib import Path
+from typing import List
 
 import pytest
 
 
+@pytest.fixture
+def example_data_dir() -> Path:
+    pkg_dir = Path(__file__).parent.parent
+    example_data_dir = pkg_dir / "example_data"
+    assert example_data_dir.exists()
+    return example_data_dir
+
+
+@pytest.fixture
+def example_audio_dir(example_data_dir: Path) -> Path:
+    example_audio_dir = example_data_dir / "audio"
+    assert example_audio_dir.exists()
+    return example_audio_dir
+
+
+@pytest.fixture
+def example_audio_files(example_audio_dir: Path) -> List[Path]:
+    audio_files = list(example_audio_dir.glob("*.[wW][aA][vV]"))
+    assert len(audio_files) == 3
+    return audio_files
+
+
 @pytest.fixture
 def data_dir() -> Path:
     dir = Path(__file__).parent / "data"

tests/test_api.py

@@ -1,14 +1,13 @@
 """Test bat detect module API."""
 
-from pathlib import Path
-
 import os
 from glob import glob
+from pathlib import Path
 
 import numpy as np
+import soundfile as sf
 import torch
 from torch import nn
-import soundfile as sf
 
 from batdetect2 import api
 
@@ -267,7 +266,6 @@ def test_process_file_with_spec_slices():
     assert len(results["spec_slices"]) == len(detections)
 
 
-
 def test_process_file_with_empty_predictions_does_not_fail(
     tmp_path: Path,
 ):

tests/test_model.py

@@ -0,0 +1,78 @@
+"""Test suite for model functions."""
+
+import warnings
+from pathlib import Path
+from typing import List
+
+import numpy as np
+from hypothesis import given, settings
+from hypothesis import strategies as st
+
+from batdetect2 import api
+from batdetect2.detector import parameters
+
+
+def test_can_import_model_without_warnings():
+    with warnings.catch_warnings():
+        warnings.simplefilter("error")
+        api.load_model()
+
+
+@settings(deadline=None, max_examples=5)
+@given(duration=st.floats(min_value=0.1, max_value=2))
+def test_can_import_model_without_pickle(duration: float):
+    # NOTE: remove this test once no other issues are found This is a temporary
+    # test to check that change in model loading did not impact model behaviour
+    # in any way.
+
+    samplerate = parameters.TARGET_SAMPLERATE_HZ
+    audio = np.random.rand(int(duration * samplerate))
+
+    model_without_pickle, model_params_without_pickle = api.load_model(
+        weights_only=True
+    )
+    model_with_pickle, model_params_with_pickle = api.load_model(
+        weights_only=False
+    )
+
+    assert model_params_without_pickle == model_params_with_pickle
+
+    predictions_without_pickle, _, _ = api.process_audio(
+        audio,
+        model=model_without_pickle,
+    )
+    predictions_with_pickle, _, _ = api.process_audio(
+        audio,
+        model=model_with_pickle,
+    )
+
+    assert predictions_without_pickle == predictions_with_pickle
+
+
+def test_can_import_model_without_pickle_on_test_data(
+    example_audio_files: List[Path],
+):
+    # NOTE: remove this test once no other issues are found This is a temporary
+    # test to check that change in model loading did not impact model behaviour
+    # in any way.
+
+    model_without_pickle, model_params_without_pickle = api.load_model(
+        weights_only=True
+    )
+    model_with_pickle, model_params_with_pickle = api.load_model(
+        weights_only=False
+    )
+
+    assert model_params_without_pickle == model_params_with_pickle
+
+    for audio_file in example_audio_files:
+        audio = api.load_audio(str(audio_file))
+        predictions_without_pickle, _, _ = api.process_audio(
+            audio,
+            model=model_without_pickle,
+        )
+        predictions_with_pickle, _, _ = api.process_audio(
+            audio,
+            model=model_with_pickle,
+        )
+        assert predictions_without_pickle == predictions_with_pickle