Winmlrunner
WinMLRunner: a command-line tool that can run.onnx or.pb models where the input and output variables are tensors or images. Download game billiard pc. It is a very handy tool to quickly validate an ONNX model. It is a very handy tool to quickly validate an ONNX model.
Sample/Tool Status All Samples [ WinmlRunner WinML Dashboard Windows ML Welcome to the Windows ML repo! Windows ML allows you to use trained machine learning models in your Windows apps (C#, C++, Javascript). 
The Windows ML inference engine evaluates trained models locally on Windows devices.
Hardware optimizations for CPU and GPU additionally enable high performance for quick evaluation results. In this repo, you will find sample apps that demonstrate how to use Windows ML to build machine learning applications, and tools that help verify models and troubleshoot issues during development on Windows 10.
For additional information on Windows ML, including step-by-step tutorials and how-to guides, please visit the. Developer Tools •: a GUI-based tool for viewing, editing, converting, and validating machine learning models for Windows ML inference engine. •: a Visual Studio extension to help you get started using WinML APIs on UWP apps by generating a template code when you add a trained ONNX file into the UWP project. From the template code you can load a model, create a session, bind inputs, and evaluate with wrapper codes. See for more info.
Download for, •: a command-line tool that can run.onnx or.pb models where the input and output variables are tensors or images. It is a very handy tool to quickly validate an ONNX model. It will attempt to load, bind, and evaluate a model and print out helpful messages. It also captures performance measurements. Sample apps These generic examples show how to use various models and input feeds with Windows ML. We have both C++ native desktop apps and C# and Javascript UWP samples •: a UWP C# app that uses the FNS-Candy style transfer model to make a cool image.
Winrunner Testing
Windrunners
•: a UWP C# app that uses the SqueezeNet model to detect the predominant object in an image. •: a UWP Javascript app that uses SqueezeNet model to detect the predominant object in an image. •: a classic desktop C++/WinRT app that uses the SqueezeNet model to detect the predominant object in an image. •: a UWP C# app that uses the MNIST model to detect numberic characters. •: a UWP C++/CX app that uses the MNIST model to detect numberic characters.