onnxruntime/docs/C_API.md

C API

Q: Why having a C API?

Q: Why not just live in C++ world? Why must C?
A: We want to distribute onnxruntime as a DLL, which can be used in .Net languages through P/Invoke. Then this is the only option we have.

Q: Is it only for .Net?
A: No. It is designed for

1. Creating language bindings for onnxruntime.e.g. C#, python, java, ...
2. Dynamic linking always has some benefits. For example, for solving diamond dependency problem.

Q: Can I export C++ types and functions across DLL or "Shared Object" Library(.so) boundaries?
A: Well, you can, but it's not a good practice. And we won't do it in this project.

What's inside

• 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.

How to use it

Include onnxruntime_c_api.h in your source code.

Then,

1. Call ONNXRuntimeInitialize
2. Create Session: ONNXRuntimeCreateInferenceSession(env, model_uri, nullptr,...)
3. Create Tensor
   1. ONNXRuntimeCreateAllocatorInfo
   2. ONNXRuntimeCreateTensorWithDataAsONNXValue
4. ONNXRuntimeRunInference