Run the same test with example data instead of random audio

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_model.py

@@ -1,6 +1,8 @@
 """Test suite for model functions."""
 
 import warnings
+from pathlib import Path
+from typing import List
 
 import numpy as np
 from hypothesis import given, settings
@@ -45,3 +47,32 @@ def test_can_import_model_without_pickle(duration: float):
     )
 
     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