NOTE: The C API is PRE-RELEASE and subject to change. Please do not rely on this file not changing.
- Creating an InferenceSession from an on-disk model file and a set of SessionOptions.
- Registering customized loggers.
- Registering customized allocators.
- Registering predefined providers and set the priority order. ONNXRuntime has a set of predefined execution providers,like CUDA, MKLDNN. User can register providers to their InferenceSession. The order of registration indicates the preference order as well.
- Running a model with inputs. These inputs must be in CPU memory, not GPU. If the model has multiple outputs, user can specify which outputs they want.
- Converting an in-memory ONNX Tensor encoded in protobuf format, to a pointer that can be used as model input.
- Setting the thread pool size for each session.
- Dynamically loading custom ops.
- Include onnxruntime_c_api.h.
- Call ONNXRuntimeInitialize
- Create Session: ONNXRuntimeCreateInferenceSession(env, model_uri, nullptr,...)
- Create Tensor
- ONNXRuntimeCreateAllocatorInfo
- ONNXRuntimeCreateTensorWithDataAsONNXValue
- ONNXRuntimeRunInference