System.Numerics.Tensors 9.0.0-rc.1.24431.7
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.
Showing the top 20 packages that depend on System.Numerics.Tensors.
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|---|---|
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LLamaSharp
LLamaSharp is a cross-platform library to run 🦙LLaMA/LLaVA model (and others) in your local device.
Based on [llama.cpp](https://github.com/ggerganov/llama.cpp), inference with LLamaSharp is efficient on both CPU and GPU.
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Based on [llama.cpp](https://github.com/ggerganov/llama.cpp), inference with LLamaSharp is efficient on both CPU and GPU.
With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.
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LLamaSharp
LLamaSharp is a cross-platform library to run 🦙LLaMA/Mtmd model (and others) in your local device.
Based on [llama.cpp](https://github.com/ggerganov/llama.cpp), inference with LLamaSharp is efficient on both CPU and GPU.
With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.
|
3 |
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.NET Framework 4.6.2
- Microsoft.Bcl.Numerics (>= 9.0.0-rc.1.24431.7)
- System.Memory (>= 4.5.5)
.NET 8.0
- No dependencies.
.NET 9.0
- No dependencies.
.NET Standard 2.0
- Microsoft.Bcl.Numerics (>= 9.0.0-rc.1.24431.7)
- System.Memory (>= 4.5.5)