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[Docker] Check torch and tf installation

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Ian Rodney 2021-04-27 00:24:23 -07:00 • committed by GitHub
parent 793145b1ab
commit fb17ef7a40
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22
ci/travis/build-docker-images.py
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@ -154,6 +154,27 @@ def _build_cpu_gpu_images(image_name, no_cache=True) -> List[str]:
return built_images
def _test_ray_ml_libraries(image_tag: str) -> None:
if "gpu" not in image_tag:
return
tf_container = DOCKER_CLIENT.containers.run(
f"rayproject/ray-ml:{image_tag}",
"python -c 'import tensorflow as tf'",
detach=True)
tf_logs = tf_container.logs().decode()
assert "Successfully opened dynamic library libcudart" in tf_logs
tf_container.stop()
torch_container = DOCKER_CLIENT.containers.run(
f"rayproject/ray-ml:{image_tag}",
"python -c 'import torch; torch.cuda.cudart()'",
detach=True)
torch_logs = torch_container.logs().decode()
assert "Torch not compiled with CUDA enabled" not in torch_logs
assert "Found no NVIDIA driver" in torch_logs
torch_container.stop()
def copy_wheels():
root_dir = _get_root_dir()
wheels = _get_wheel_name(None)
@ -214,6 +235,7 @@ def build_ray_ml():
tag = img.split(":")[-1]
DOCKER_CLIENT.api.tag(
image=img, repository="rayproject/autoscaler", tag=tag)
_test_ray_ml_libraries(tag)
def _get_docker_creds() -> Tuple[str, str]: