.NET bindings for the Pytorch engine

Matteo Interlandi

Last update: Aug 30, 2021

Related tags

Deep Learning TorchSharp

Overview

TorchSharp

TorchSharp is a .NET library that provides access to the library that powers PyTorch. It is a work in progress, but already provides a .NET API that can be used to perform (1) various operations on ATen Tensors; (2) scoring of TorchScript models; (3) Training of simple neural networks.

Our current focus is to bind the entire API surfaced by libtorch.

Things that you can try:

using AtenSharp;

var x = new FloatTensor (100);   // 1D-tensor with 100 elements
FloatTensor result = new FloatTensor (100);

FloatTensor.Add (x, 23, result);

Console.WriteLine (x [12]);

Discussions

We have a chat room on Gitter

Building

Windows

Requirements:

Visual Studio
git
cmake (tested with 3.14)

Commands:

Building: build.cmd
Building from Visual Studio: first build using the command line
See all configurations: build.cmd -?
Run tests from command line: build.cmd -runtests
Build packages: build.cmd -buildpackages

Linux/Mac

Requirements:

requirements to run .NET Core 2.0
git
cmake (tested with 3.14)
clang 3.9

Example to fulfill the requirements in Ubuntu 16:

sudo apt-get update
sudo apt-get install git clang cmake libunwind8 curl
sudo apt-get install libssl1.0.0
sudo apt-get install libomp-dev

Commands:

Building: ./build.sh
Building from Visual Studio: first build using the command line
See all configurations: ./build.sh -?
Run tests from command line: ./build.sh -runtests
Build packages: ./build.sh -buildpackages

Updating package version for new release

To change the package version update this file. Everything is currently considered in preview.

Use the following two MSBuild arguments in order to control the -preview and the build numbers in the name of the nuget packages produced (use one of the two generally):

Name	Value	Example Version Output
StabilizePackageVersion	true	1.0.0
IncludeBuildNumberInPackageVersion	false	1.0.0-preview

Sample command: ./build.cmd -release -buildpackages -- /p:StabilizePackageVersion=true

GPU support

For GPU support it is required to install CUDA 9.0 and make it available to the dynamic linker.

Examples

Porting of the more famous network architectures to TorchSharp is in progress. For the moment we only support MNIST and AlexNet

Comments

When will an official release and nuget package be available?

Hi @interesaaat,

Thanks for the big effort to bring training to TorchSharp. Do you have a rough estimate of when all your efforts will be merged to xamarin/TorchSharp, and release on nuget?

Best regards Mads

opened by mdabros 4
Loss function class
In Pytorch loss functions in torch.nn work as follows:

loss = NLLLoss(SOME PARAMETERS IF NEEDED) prediction = model.forward(input) output = loss(prediction, target)

We should match the behavior where once initialized the loss can be applied to the prediction and the target tensors.
opened by artidoro 2
Add tensor transfer functions between CPU and CUDA devices

This PR adds functions for transferring tensors between CPU and CUDA devices. I commented this line to avoid build error. We need to extend this transfer function later to support multiple CUDA devices (e.g., "cuda:3").

opened by gyeongin 0
Error when running the template TorchTensorType.tt

When you right click and Run Custom Tool, it should generate the .cs file. If it is not currently set up to do so, could can delete the .tt file and add it back to the solution.

When I try to run the template using the Run Custom Tool it gives me an error.

Could you fix it? (or maybe we don't need the template?)

opened by artidoro 1

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