wip

.github/workflows/ci.yml

@@ -14,9 +14,12 @@ jobs:
       - name: build image
         run: make build
 
-      - name: test image
+      - name: test
         run: make test
 
+      - name: test-no-gpu
+        run: make test-no-gpu
+
       # - name: push image
       #   if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
       #   run: make push

Makefile

@@ -12,7 +12,16 @@ push:
 .PHONY: test
 test: build
 	docker run --rm -t --gpus all \
-	-e PITCH_DETECTORS_ERROR_GPU_NOT_AVAILABLE=true \
+	-e PITCH_DETECTORS_GPU=true \
+	-v $$PWD/pitch_detectors:/app/pitch_detectors \
+	-v $$PWD/tests:/app/tests \
+	tandav/pitch-detectors:11.8.0-cudnn8-devel-ubuntu22.04 \
+	pytest -v --cov pitch_detectors --cov-fail-under 90
+
+.PHONY: test-no-gpu
+test-no-gpu: build
+	docker run --rm -t \
+	-e PITCH_DETECTORS_GPU=false \
 	-v $$PWD/pitch_detectors:/app/pitch_detectors \
 	-v $$PWD/tests:/app/tests \
 	tandav/pitch-detectors:11.8.0-cudnn8-devel-ubuntu22.04 \

pitch_detectors/algorithms.py

@@ -18,7 +18,7 @@ def __init__(self, a: np.ndarray, fs: int, hz_min: float = 75, hz_max: float = 6
         self.f0: tp.Optional[np.ndarray] = None
         self.t: tp.Optional[np.ndarray] = None
         if (
-            os.environ.get('PITCH_DETECTORS_ERROR_GPU_NOT_AVAILABLE') and
+            os.environ.get('PITCH_DETECTORS_GPU') == 'true' and
             self.use_gpu and
             not self.gpu_available()
         ):
@@ -128,8 +128,6 @@ def __init__(
             torch.device(device)
 
         super().__init__(a, fs, hz_min, hz_max)
-        if not torch.cuda.is_available():
-            raise RuntimeError('TorchCrepe requires a GPU')
 
         f0, confidence = torchcrepe.predict(
             torch.from_numpy(a[np.newaxis, ...]),

tests/gpu_test.py

@@ -1,3 +1,4 @@
+import os
 import subprocess
 
 import pytest
@@ -6,15 +7,18 @@
 
 
 @pytest.mark.order(0)
+@pytest.mark.skipif(os.environ.get('PITCH_DETECTORS_GPU') == 'false', reason='gpu is not used')
 def test_nvidia_smi():
     subprocess.check_call('nvidia-smi')
 
 
 @pytest.mark.order(1)
+@pytest.mark.skipif(os.environ.get('PITCH_DETECTORS_GPU') == 'false', reason='gpu is not used')
 def test_tensorflow():
     assert tf.config.experimental.list_physical_devices('GPU')
 
 
 @pytest.mark.order(2)
+@pytest.mark.skipif(os.environ.get('PITCH_DETECTORS_GPU') == 'false', reason='gpu is not used')
 def test_pytorch():
     assert torch.cuda.is_available()