onnxruntime/docs/C_API.md
jignparm 4635bcc624 Updating C_API end-to-end test and user samples (#564)
* Updating user sample and C_API unit test

* remove debugging info

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* header file location changed in master...updating
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C API

Features

  • 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.

Usage Overview

  1. Include onnxruntime_c_api.h.
  2. Call OrtCreateEnv
  3. Create Session: OrtCreateSession(env, model_uri, nullptr,...)
  4. Create Tensor
    1. OrtCreateAllocatorInfo
    2. OrtCreateTensorWithDataAsOrtValue
  5. OrtRun

Sample code

The example below shows a sample run using the SqueezeNet model from ONNX model zoo, including dynamically reading model inputs, outputs, shape and type information, as well as running a sample vector and fetching the resulting class probabilities for inspection.