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Add cuda resnet50 test to smoke test #7020

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Merged
atalman merged 3 commits into from
Dec 8, 2022
Merged

Add cuda resnet50 test to smoke test #7020

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9563a40
Add cuda resnet50 test
atalman Dec 8, 2022
06b55d4
Fix path
atalman Dec 8, 2022
58a305f
Tune vision smoke test
atalman Dec 8, 2022
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18 changes: 9 additions & 9 deletions test/smoke_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,6 @@ def smoke_test_torchvision() -> None:
all(x is not None for x in [torch.ops.image.decode_png, torch.ops.torchvision.roi_align]),
)


def smoke_test_torchvision_read_decode() -> None:
img_jpg = read_image(str(SCRIPT_DIR / "assets" / "encode_jpeg" / "grace_hopper_517x606.jpg"))
if img_jpg.ndim != 3 or img_jpg.numel() < 100:
Expand All @@ -26,13 +25,12 @@ def smoke_test_torchvision_read_decode() -> None:
if img_png.ndim != 3 or img_png.numel() < 100:
raise RuntimeError(f"Unexpected shape of img_png: {img_png.shape}")


def smoke_test_torchvision_resnet50_classify() -> None:
img = read_image(str(SCRIPT_DIR / ".." / "gallery" / "assets" / "dog2.jpg"))
def smoke_test_torchvision_resnet50_classify(device: str = "cpu") -> None:
img = read_image(str(SCRIPT_DIR / ".." / "gallery" / "assets" / "dog2.jpg")).to(device)

# Step 1: Initialize model with the best available weights
weights = ResNet50_Weights.DEFAULT
model = resnet50(weights=weights)
model = resnet50(weights=weights).to(device)
model.eval()

# Step 2: Initialize the inference transforms
Expand All @@ -47,17 +45,19 @@ def smoke_test_torchvision_resnet50_classify() -> None:
score = prediction[class_id].item()
category_name = weights.meta["categories"][class_id]
expected_category = "German shepherd"
print(f"{category_name}: {100 * score:.1f}%")
print(f"{category_name} ({device}): {100 * score:.1f}%")
if category_name != expected_category:
raise RuntimeError(f"Failed ResNet50 classify {category_name} Expected: {expected_category}")

raise RuntimeError(
f"Failed ResNet50 classify {category_name} Expected: {expected_category}"
)

def main() -> None:
print(f"torchvision: {torchvision.__version__}")
smoke_test_torchvision()
smoke_test_torchvision_read_decode()
smoke_test_torchvision_resnet50_classify()

if torch.cuda.is_available():
smoke_test_torchvision_resnet50_classify("cuda")

if __name__ == "__main__":
main()