def validate_provider_availability()

in optimum/onnxruntime/utils.py [0:0]

• 40 lines of code
• 17 McCabe index (conditional complexity)

def validate_provider_availability(provider: str):
    """
    Ensure the ONNX Runtime execution provider `provider` is available, and raise an error if it is not.

    Args:
        provider (str): Name of an ONNX Runtime execution provider.
    """
    # Disable on Windows as reported in https://github.com/huggingface/optimum/issues/769.
    # Disable as well for ORT 1.16.0 that has changed changed the way _ld_preload.py is filled: https://github.com/huggingface/optimum/issues/1402.
    if (
        version.parse(ort.__version__) < version.parse("1.16.0")
        and os.name != "nt"
        and provider in ["CUDAExecutionProvider", "TensorrtExecutionProvider"]
    ):
        path_cuda_lib = os.path.join(ort.__path__[0], "capi", "libonnxruntime_providers_cuda.so")
        path_trt_lib = os.path.join(ort.__path__[0], "capi", "libonnxruntime_providers_tensorrt.so")
        path_dependecy_loading = os.path.join(ort.__path__[0], "capi", "_ld_preload.py")

        with open(path_dependecy_loading, "r") as f:
            file_string = f.read()

            if "ORT_CUDA" not in file_string or "ORT_TENSORRT" not in file_string:
                if os.path.isfile(path_cuda_lib) and os.path.isfile(path_trt_lib):
                    raise ImportError(
                        f"`onnxruntime-gpu` is installed, but GPU dependencies are not loaded. It is likely there is a conflicting install between `onnxruntime` and `onnxruntime-gpu`. Please install only `onnxruntime-gpu` in order to use {provider}."
                    )
                elif os.path.isfile(path_cuda_lib) and is_onnxruntime_training_available():
                    if provider == "TensorrtExecutionProvider":
                        raise ImportError(
                            f"Asked to use {provider}, but `onnxruntime-training` package doesn't support {provider}. Please use `CUDAExecutionProvider` instead."
                        )
                else:
                    raise ImportError(
                        f"Asked to use {provider}, but `onnxruntime-gpu` package was not found. Make sure to install `onnxruntime-gpu` package instead of `onnxruntime`."
                    )

            if provider == "CUDAExecutionProvider":
                if os.environ.get("ORT_CUDA_UNAVAILABLE", "0") == "1":
                    raise ImportError(
                        "`onnxruntime-gpu` package is installed, but CUDA requirements could not be loaded. Make sure to meet the required dependencies: https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html"
                    )
            if provider == "TensorrtExecutionProvider":
                if os.environ.get("ORT_TENSORRT_UNAVAILABLE", "0") == "1":
                    raise ImportError(
                        "`onnxruntime-gpu` package is installed, but TensorRT requirements could not be loaded. Make sure to meet the required dependencies following https://onnxruntime.ai/docs/execution-providers/TensorRT-ExecutionProvider.html and https://hf.co/docs/optimum/onnxruntime/usage_guides/gpu#tensorrtexecutionprovider ."
                    )

    available_providers = ort.get_available_providers()
    if provider not in available_providers:
        raise ValueError(
            f"Asked to use {provider} as an ONNX Runtime execution provider, but the available execution providers are {available_providers}."
        )