System.Numerics.Tensors
8.0.0
Prefix Reserved
.NET 6.0
This package targets .NET 6.0. The package is compatible with this framework or higher.
.NET Standard 2.0
This package targets .NET Standard 2.0. The package is compatible with this framework or higher.
.NET Framework 4.6.2
This package targets .NET Framework 4.6.2. The package is compatible with this framework or higher.
There is a newer prerelease version of this package available.
See the version list below for details.
See the version list below for details.
dotnet add package System.Numerics.Tensors --version 8.0.0
NuGet\Install-Package System.Numerics.Tensors -Version 8.0.0
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="System.Numerics.Tensors" Version="8.0.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add System.Numerics.Tensors --version 8.0.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: System.Numerics.Tensors, 8.0.0"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install System.Numerics.Tensors as a Cake Addin #addin nuget:?package=System.Numerics.Tensors&version=8.0.0 // Install System.Numerics.Tensors as a Cake Tool #tool nuget:?package=System.Numerics.Tensors&version=8.0.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
About
Provides methods for performing mathematical operations over tensors represented as spans. These methods are accelerated to use SIMD (Single instruction, multiple data) operations supported by the CPU where available.
Key Features
- Numerical operations on tensors represented as
ReadOnlySpan<float> - Element-wise arithmetic: Add, Subtract, Multiply, Divide, Exp, Log, Cosh, Tanh, etc.
- Tensor arithmetic: CosineSimilarity, Distance, Dot, Normalize, Softmax, Sigmoid, etc.
How to Use
using System.Numerics.Tensors;
var movies = new[] {
new { Title="The Lion King", Embedding= new [] { 0.10022575f, -0.23998135f } },
new { Title="Inception", Embedding= new [] { 0.10327095f, 0.2563685f } },
new { Title="Toy Story", Embedding= new [] { 0.095857024f, -0.201278f } },
new { Title="Pulp Function", Embedding= new [] { 0.106827796f, 0.21676421f } },
new { Title="Shrek", Embedding= new [] { 0.09568083f, -0.21177962f } }
};
var queryEmbedding = new[] { 0.12217915f, -0.034832448f };
var top3MoviesTensorPrimitives =
movies
.Select(movie =>
(
movie.Title,
Similarity: TensorPrimitives.CosineSimilarity(queryEmbedding, movie.Embedding)
))
.OrderByDescending(movies => movies.Similarity)
.Take(3);
foreach (var movie in top3MoviesTensorPrimitives)
{
Console.WriteLine(movie);
}
Main Types
The main types provided by this library are:
System.Numerics.Tensors.TensorPrimitives
Additional Documentation
Feedback & Contributing
System.Numerics.Tensors is released as open source under the MIT license. Bug reports and contributions are welcome at the GitHub repository.
| Product | Versions Compatible and additional computed target framework versions. |
|---|---|
| .NET | net5.0 was computed. net5.0-windows was computed. net6.0 is compatible. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 is compatible. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 is compatible. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
| .NET Core | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
| .NET Standard | netstandard2.0 is compatible. netstandard2.1 was computed. |
| .NET Framework | net461 was computed. net462 is compatible. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed. |
| MonoAndroid | monoandroid was computed. |
| MonoMac | monomac was computed. |
| MonoTouch | monotouch was computed. |
| Tizen | tizen40 was computed. tizen60 was computed. |
| Xamarin.iOS | xamarinios was computed. |
| Xamarin.Mac | xamarinmac was computed. |
| Xamarin.TVOS | xamarintvos was computed. |
| Xamarin.WatchOS | xamarinwatchos was computed. |
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.
-
.NETFramework 4.6.2
- Microsoft.Bcl.Numerics (>= 8.0.0)
- System.Memory (>= 4.5.5)
-
.NETStandard 2.0
- Microsoft.Bcl.Numerics (>= 8.0.0)
- System.Memory (>= 4.5.5)
-
net6.0
- No dependencies.
-
net7.0
- No dependencies.
-
net8.0
- No dependencies.
NuGet packages (25)
Showing the top 5 NuGet packages that depend on System.Numerics.Tensors:
| Package | Downloads |
|---|---|
|
Microsoft.ML.CpuMath
Microsoft.ML.CpuMath contains optimized math routines for ML.NET. |
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This package contains easy-to-use and high-performance libraries for data analysis and transformation. |
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Kernel Memory is a Copilot/Semantic Kernel Plugin and Memory Web Service to index and query any data and documents, using LLM and natural language, tracking sources and showing citations. The package contains the interfaces and models shared by all Kernel Memory packages. |
GitHub repositories (17)
Showing the top 5 popular GitHub repositories that depend on System.Numerics.Tensors:
| Repository | Stars |
|---|---|
|
microsoft/semantic-kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
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ML.NET is an open source and cross-platform machine learning framework for .NET.
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ppy/osu-framework
A game framework written with osu! in mind.
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microsoft/kernel-memory
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
|