Tensor 0.4.11

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.

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"
For F# scripts that support #r syntax, copy this into the source code to reference the package.

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 History

Version Downloads Last updated
0.4.11 2,147 5/8/2018
0.4.11-v0.4.11-215 344 5/8/2018
0.4.11-symtensor-core-242 401 11/15/2018
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0.4.11-symtensor-core-231 390 11/9/2018
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0.4.11-symtensor-core-229 361 11/8/2018
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0.4.11-symtensor-core-227 407 10/30/2018
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0.4.11-symtensor-core-225 357 10/30/2018
0.4.11-develop-216 499 5/8/2018
0.4.10-develop-213 509 5/8/2018
0.4.10-develop-212 487 5/7/2018
0.4.10-develop-211 502 5/7/2018
0.3.0.712-master 462 9/1/2017
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