Tensor 0.4.11

.NET Standard 2.0
Install-Package Tensor -Version 0.4.11
dotnet add package Tensor --version 0.4.11
<PackageReference Include="Tensor" Version="0.4.11" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Tensor --version 0.4.11
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: Tensor, 0.4.11"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install Tensor as a Cake Addin
#addin nuget:?package=Tensor&version=0.4.11

// Install Tensor as a Cake Tool
#tool nuget:?package=Tensor&version=0.4.11
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Tensor (n-dimensional array) library for F#

     Core features:
       - n-dimensional arrays (tensors) in host memory or on CUDA GPUs
       - element-wise operations (addition, multiplication, absolute value, etc.)
       - basic linear algebra operations (dot product, SVD decomposition, matrix inverse, etc.)
       - reduction operations (sum, product, average, maximum, arg max, etc.)
       - logic operations (comparision, and, or, etc.)
       - views, slicing, reshaping, broadcasting (similar to NumPy)
       - scatter and gather by indices
       - standard functional operations (map, fold, etc.)

     Data exchange:
       - read/write support for HDF5 (.h5)
       - interop with standard F# types (Seq, List, Array, Array2D, Array3D, etc.)

     Performance:
       - host: SIMD and BLAS accelerated operations
         - by default Intel MKL is used (shipped with NuGet package)
         - other BLASes (OpenBLAS, vendor-specific) can be selected by configuration option
       - CUDA GPU: all operations performed locally on GPU and cuBLAS used for matrix operations

     Requirements:
       - Linux, MacOS or Windows on x64
       - Linux requires libgomp.so.1 installed.

     Additional algorithms are provided in the Tensor.Algorithm package.

Product Versions
.NET net5.0 net5.0-windows net6.0 net6.0-android net6.0-ios net6.0-maccatalyst net6.0-macos net6.0-tvos net6.0-windows
.NET Core netcoreapp2.0 netcoreapp2.1 netcoreapp2.2 netcoreapp3.0 netcoreapp3.1
.NET Standard netstandard2.0 netstandard2.1
.NET Framework net461 net462 net463 net47 net471 net472 net48
MonoAndroid monoandroid
MonoMac monomac
MonoTouch monotouch
Tizen tizen40 tizen60
Xamarin.iOS xamarinios
Xamarin.Mac xamarinmac
Xamarin.TVOS xamarintvos
Xamarin.WatchOS xamarinwatchos
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (3)

Showing the top 3 NuGet packages that depend on Tensor:

Package Downloads
DeepNet

Deep learning library for F#. Provides symbolic model differentiation, automatic differentiation and compilation to CUDA GPUs. Includes optimizers and model blocks used in deep learning. Make sure to set the platform of your project to x64.

RPlotTools

Tools for plotting using R from F#.

Tensor.Algorithm

Data types: - arbitrary precision rational numbers Matrix algebra (integer, rational): - Row echelon form - Smith normal form - Kernel, cokernel and (pseudo-)inverse Matrix decomposition (floating point): - Principal component analysis (PCA) - ZCA whitening Misc: - Bezout's identity - Loading of NumPy's .npy and .npz files.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
0.4.11 5,067 5/8/2018
0.4.11-v0.4.11-215 523 5/8/2018
0.4.11-symtensor-core-242 619 11/15/2018
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0.4.11-symtensor-core-236 557 11/14/2018
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0.4.11-symtensor-core-231 580 11/9/2018
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0.4.11-symtensor-core-227 607 10/30/2018
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0.4.11-symtensor-core-225 543 10/30/2018
0.4.11-develop-216 761 5/8/2018
0.4.10-develop-213 764 5/8/2018
0.4.10-develop-212 750 5/7/2018
0.4.10-develop-211 772 5/7/2018
0.3.0.712-master 631 9/1/2017
0.3.0.711-master 636 9/1/2017
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0.2.0.431-master 736 12/2/2016
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