onnxruntime/docs/CSharp_API.md

ONNX Runtime C# API

The ONNX runtime provides a C# .Net binding for running inference on ONNX models in any of the .Net standard platforms. The API is .Net standard 1.1 compliant for maximum portability. This document describes the API.

NuGet Package

There is a NuGet package Microsoft.ML.OnnxRuntime available for .Net consumers, which includes the prebuilt binaries for ONNX runtime. The API is portable across all platforms and architectures supported by the .Net standard, although currently the NuGet package contains the prebuilt binaries for Windows 10 platform on x64 CPUs only.

Getting Started

Here is simple tutorial for getting started with running inference on an existing ONNX model for a given input data (a.k.a query). Say the model is trained using any of the well-known training frameworks and exported as an ONNX model into a file named model.onnx. The runtime incarnation of a model is an InferenceSession object. You simply construct an InferenceSession object using the model file as parameter --

var session = new InferenceSession("model.onnx");

Once a session is created, you can run queries on the session using your input data, using the Run method of the InferenceSession. Both input and output of Run method are represented as collections of .Net Tensor objects (as defined in System.Numerics.Tensor) -

Tensor<float> t1, t2;  // let's say data is fed into the Tensor objects
var inputs = new List<NamedOnnxValue>()
             {
                NamedOnnxValue.CreateFromTensor<float>("name1", t1),
                NamedOnnxValue.CreateFromTensor<float>("name2", t2)
             };
IReadOnlyCollection<NamedOnnxValue> results = session.Run(inputs);

You can load your input data into Tensor objects in several ways. A simple example is to create the Tensor from arrays - float[] sourceData; // assume your data is loaded into a flat float array int[] dimensions; // and the dimensions of the input is stored here Tensor t1 = new DenseTensor(sourceData, dimensions);

Here is a complete sample code that runs inference on a pretrained model.

API Reference

InferenceSession

class InferenceSession: IDisposable

The runtime representation of an ONNX model

Constructor

InferenceSession(string modelPath);
InferenceSession(string modelPath, SesionOptions options);

Properties

IReadOnlyDictionary<NodeMetadata> InputMetadata;    

Data types and shapes of the input nodes of the model.
IReadOnlyDictionary OutputMetadata; Data types and shapes of the output nodes of the model.

Methods

IReadOnlyCollection<NamedOnnxValue> Run(IReadOnlyCollection<NamedOnnxValue> inputs);

Runs the model with the given input data to compute all the output nodes and returns the output node values. Both input and output are collection of NamedOnnxValue, which in turn is a name-value pair of string names and Tensor values.

IReadOnlyCollection<NamedOnnxValue> Run(IReadOnlyCollection<NamedOnnxValue> inputs, IReadOnlyCollection<string> desiredOutputNodes);

Runs the model on given inputs for the given output nodes only.

System.Numerics.Tensor

The primary .Net object that is used for holding input-output of the model inference. Details on this newly introduced data type can be found in its open-source implementation. The binaries are available as a .Net NuGet package.

NamedOnnxValue

class NamedOnnxValue;

Represents a name-value pair of string names and any type of value that ONNX runtime supports as input-output data. Currently, only Tensor objects are supported as input-output values.

Constructor

No public constructor available.

Properties

string Name;   // read only

Methods

static NamedOnnxValue CreateFromTensor<T>(string name, Tensor<T>);

Creates a NamedOnnxValue from a name and a Tensor object.

Tensor<T> AsTensor<T>();

Accesses the value as a Tensor. Returns null if the value is not a Tensor.

SessionOptions

class SessionOptions: IDisposable;

A collection of properties to be set for configuring the OnnxRuntime session

Constructor

SessionOptions();

Constructs a SessionOptions will all options at default/unset values.

Properties

static SessionOptions Default;   //read-only

Accessor to the default static option object

Methods

AppendExecutionProvider(ExecutionProvider provider);

Appends execution provider to the session. For any operator in the graph the first execution provider that implements the operator will be user. ExecutionProvider is defined as the following enum -

enum ExecutionProvider
{
    Cpu,
    MklDnn
}

NodeMetadata

Container of metadata for a model graph node, used for communicating the shape and type of the input and output nodes.

Properties

int[] Dimensions;  

Read-only shape of the node, when the node is a Tensor. Undefined if the node is not a Tensor.

System.Type ElementType;

Type of the elements of the node, when node is a Tensor. Undefined for non-Tensor nodes.

bool IsTensor;

Whether the node is a Tensor

Exceptions

class OnnxRuntimeException: Exception;

The type of Exception that is thrown in most of the error conditions related to Onnx Runtime.