DiffSharp.Backends.Torch 1.0.0-preview-1177844564

This is a prerelease version of DiffSharp.Backends.Torch.
There is a newer version of this package available.
See the version list below for details.
dotnet add package DiffSharp.Backends.Torch --version 1.0.0-preview-1177844564
                    
NuGet\Install-Package DiffSharp.Backends.Torch -Version 1.0.0-preview-1177844564
                    
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="DiffSharp.Backends.Torch" Version="1.0.0-preview-1177844564" />
                    
For projects that support PackageReference, copy this XML node into the project file to reference the package.
<PackageVersion Include="DiffSharp.Backends.Torch" Version="1.0.0-preview-1177844564" />
                    
Directory.Packages.props
<PackageReference Include="DiffSharp.Backends.Torch" />
                    
Project file
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package.
paket add DiffSharp.Backends.Torch --version 1.0.0-preview-1177844564
                    
#r "nuget: DiffSharp.Backends.Torch, 1.0.0-preview-1177844564"
                    
#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.
#:package DiffSharp.Backends.Torch@1.0.0-preview-1177844564
                    
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package.
#addin nuget:?package=DiffSharp.Backends.Torch&version=1.0.0-preview-1177844564&prerelease
                    
Install as a Cake Addin
#tool nuget:?package=DiffSharp.Backends.Torch&version=1.0.0-preview-1177844564&prerelease
                    
Install as a Cake Tool

Package Description

Product Compatible and additional computed target framework versions.
.NET net5.0 is compatible.  net5.0-windows was computed.  net6.0 was computed.  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 was computed.  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 was computed.  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.  net9.0 was computed.  net9.0-android was computed.  net9.0-browser was computed.  net9.0-ios was computed.  net9.0-maccatalyst was computed.  net9.0-macos was computed.  net9.0-tvos was computed.  net9.0-windows was computed.  net10.0 was computed.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (5)

Showing the top 5 NuGet packages that depend on DiffSharp.Backends.Torch:

Package Downloads
DiffSharp-cuda-windows

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

DiffSharp-cuda-linux

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

DiffSharp-cpu

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

DiffSharp-lite

DiffSharp is a tensor library with support for differentiable programming. It is designed for use in machine learning, probabilistic programming, optimization and other domains. For documentation and installation instructions visit: https://diffsharp.github.io/

FAkka.Mathnet.Symbolic.withTensorSupported

Package Description

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
1.0.7 6,493 3/26/2022
1.0.7-preview2044360861 601 3/26/2022
1.0.7-preview1873603133 657 2/21/2022
1.0.7-preview1872895008 646 2/20/2022
1.0.7-preview1872194677 650 2/20/2022
1.0.7-preview1867437105 631 2/19/2022
1.0.7-preview1838897476 631 2/14/2022
1.0.7-preview1838869913 632 2/14/2022
1.0.6 6,865 2/9/2022
1.0.6-preview1838805210 630 2/14/2022
1.0.6-preview1838790927 706 2/14/2022
1.0.6-preview1838781533 629 2/14/2022
1.0.6-preview1838761310 660 2/14/2022
1.0.6-preview1838574327 718 2/14/2022
1.0.6-preview1838238393 655 2/13/2022
1.0.6-preview1837967313 691 2/13/2022
1.0.6-preview1837932839 461 2/13/2022
1.0.6-preview1837857091 461 2/13/2022
1.0.5 3,804 2/9/2022
1.0.4 3,969 2/8/2022
1.0.3 5,066 2/8/2022
1.0.2 4,183 2/8/2022
1.0.1 5,030 11/8/2021
1.0.0-preview-987646120 797 6/30/2021
1.0.0-preview-964642900 766 6/23/2021
1.0.0-preview-964597118 593 6/23/2021
1.0.0-preview-964532207 659 6/23/2021
1.0.0-preview-964414624 666 6/23/2021
1.0.0-preview-962665709 516 6/23/2021
1.0.0-preview-961120541 561 6/22/2021
1.0.0-preview-958984202 599 6/22/2021
1.0.0-preview-783523654 745 4/25/2021
1.0.0-preview-783503343 650 4/25/2021
1.0.0-preview-783410550 682 4/25/2021
1.0.0-preview-781810429 629 4/25/2021
1.0.0-preview-775752139 719 4/22/2021
1.0.0-preview-774228953 684 4/22/2021
1.0.0-preview-769092916 667 4/21/2021
1.0.0-preview-768013090 648 4/20/2021
1.0.0-preview-762002995 635 4/19/2021
1.0.0-preview-761040762 699 4/18/2021
1.0.0-preview-761018834 706 4/18/2021
1.0.0-preview-756065403 602 4/16/2021
1.0.0-preview-755638011 630 4/16/2021
1.0.0-preview-752421465 666 4/15/2021
1.0.0-preview-748176085 662 4/14/2021
1.0.0-preview-746203897 636 4/13/2021
1.0.0-preview-746138300 663 4/13/2021
1.0.0-preview-745205599 619 4/13/2021
1.0.0-preview-739671157 646 4/12/2021
1.0.0-preview-712483117 649 4/2/2021
1.0.0-preview-699281085 595 3/29/2021
1.0.0-preview-699125312 652 3/29/2021
1.0.0-preview-698458610 699 3/29/2021
1.0.0-preview-697743517 710 3/29/2021
1.0.0-preview-697665469 650 3/29/2021
1.0.0-preview-690194555 652 3/26/2021
1.0.0-preview-688124591 632 3/25/2021
1.0.0-preview-687886352 628 3/25/2021
1.0.0-preview-681551353 651 3/24/2021
1.0.0-preview-681104545 682 3/23/2021
1.0.0-preview-680643606 723 3/23/2021
1.0.0-preview-679950457 646 3/23/2021
1.0.0-preview-669022451 660 3/19/2021
1.0.0-preview-643151273 556 3/11/2021
1.0.0-preview-633398743 622 3/8/2021
1.0.0-preview-633348953 654 3/8/2021
1.0.0-preview-621803110 694 3/4/2021
1.0.0-preview-611561611 687 3/1/2021
1.0.0-preview-611172961 599 3/1/2021
1.0.0-preview-593196134 570 2/23/2021
1.0.0-preview-589424126 615 2/22/2021
1.0.0-preview-589402583 646 2/22/2021
1.0.0-preview-586837684 601 2/21/2021
1.0.0-preview-586440747 655 2/21/2021
1.0.0-preview-498549439 654 1/20/2021
1.0.0-preview-485581354 691 1/14/2021
1.0.0-preview-392545720 759 11/30/2020
1.0.0-preview-392233243 704 11/30/2020
1.0.0-preview-392187079 774 11/30/2020
1.0.0-preview-390203270 696 11/29/2020
1.0.0-preview-387146713 790 11/27/2020
1.0.0-preview-386097798 826 11/26/2020
1.0.0-preview-385867359 830 11/26/2020
1.0.0-preview-385523380 709 11/26/2020
1.0.0-preview-384128234 820 11/25/2020
1.0.0-preview-374537774 779 11/20/2020
1.0.0-preview-374468367 673 11/20/2020
1.0.0-preview-368681212 737 11/17/2020
1.0.0-preview-368659044 826 11/17/2020
1.0.0-preview-364746088 858 11/15/2020
1.0.0-preview-364706087 791 11/15/2020
1.0.0-preview-363372268 710 11/14/2020
1.0.0-preview-362038354 754 11/13/2020
1.0.0-preview-362004577 747 11/13/2020
1.0.0-preview-361488593 697 11/13/2020
1.0.0-preview-360710530 740 11/13/2020
1.0.0-preview-359756455 730 11/12/2020
1.0.0-preview-358333968 787 11/11/2020
1.0.0-preview-358184921 788 11/11/2020
1.0.0-preview-358174946 753 11/11/2020
1.0.0-preview-349704450 847 11/6/2020
1.0.0-preview-349564717 826 11/6/2020
1.0.0-preview-343634015 839 11/3/2020
1.0.0-preview-343610434 749 11/3/2020
1.0.0-preview-328097867 1,046 10/26/2020
1.0.0-preview-322875134 787 10/22/2020
1.0.0-preview-315311536 734 10/19/2020
1.0.0-preview-309180753 773 10/15/2020
1.0.0-preview-309013019 809 10/15/2020
1.0.0-preview-308920132 719 10/15/2020
1.0.0-preview-308837132 782 10/15/2020
1.0.0-preview-308751690 747 10/15/2020
1.0.0-preview-308593840 763 10/15/2020
1.0.0-preview-299173506 846 10/10/2020
1.0.0-preview-292259854 853 10/6/2020
1.0.0-preview-291985511 800 10/6/2020
1.0.0-preview-291903007 774 10/6/2020
1.0.0-preview-291722399 801 10/6/2020
1.0.0-preview-284981464 749 10/2/2020
1.0.0-preview-284595614 735 10/2/2020
1.0.0-preview-280886714 806 9/30/2020
1.0.0-preview-278989673 748 9/29/2020
1.0.0-preview-277686264 747 9/29/2020
1.0.0-preview-277653295 754 9/29/2020
1.0.0-preview-275730148 819 9/28/2020
1.0.0-preview-275727262 788 9/28/2020
1.0.0-preview-267667710 837 9/22/2020
1.0.0-preview-263264614 846 9/20/2020
1.0.0-preview-263250971 866 9/20/2020
1.0.0-preview-262623253 738 9/19/2020
1.0.0-preview-258339834 779 9/16/2020
1.0.0-preview-258210544 806 9/16/2020
1.0.0-preview-258177528 847 9/16/2020
1.0.0-preview-258119380 849 9/16/2020
1.0.0-preview-256594931 801 9/16/2020
1.0.0-preview-256435175 874 9/15/2020
1.0.0-preview-253816091 770 9/14/2020
1.0.0-preview-253197654 793 9/14/2020
1.0.0-preview-247523274 734 9/10/2020
1.0.0-preview-247118168 816 9/9/2020
1.0.0-preview-246444372 861 9/9/2020
1.0.0-preview-246434361 821 9/9/2020
1.0.0-preview-246402060 743 9/9/2020
1.0.0-preview-245105781 757 9/8/2020
1.0.0-preview-244918410 825 9/8/2020
1.0.0-preview-243478925 741 9/7/2020
1.0.0-preview-243471084 782 9/7/2020
1.0.0-preview-243323135 881 9/7/2020
1.0.0-preview-1413494063 685 11/2/2021
1.0.0-preview-1405354284 622 10/31/2021
1.0.0-preview-1338129467 676 10/13/2021
1.0.0-preview-1327345305 768 10/11/2021
1.0.0-preview-1325686991 612 10/10/2021
1.0.0-preview-1324682939 758 10/10/2021
1.0.0-preview-1239345497 689 9/15/2021
1.0.0-preview-1227879651 668 9/13/2021
1.0.0-preview-1227810778 672 9/13/2021
1.0.0-preview-1222163389 660 9/10/2021
1.0.0-preview-1177844564 705 8/28/2021
1.0.0-preview-1176119659 611 8/28/2021
1.0.0-preview-1176116073 621 8/28/2021
1.0.0-preview-1176112166 589 8/28/2021
1.0.0-preview-1172193368 608 8/26/2021
1.0.0-preview-1168287221 597 8/25/2021
1.0.0-preview-1147185155 688 8/19/2021
1.0.0-preview-1133286135 730 8/15/2021
1.0.0-preview-1118120224 700 8/10/2021
1.0.0-preview-1111420036 613 8/9/2021
1.0.0-preview-1111385512 547 8/9/2021
1.0.0-preview-1111166736 605 8/9/2021
1.0.0-preview-1088380884 636 8/1/2021
1.0.0-preview-1088311063 642 8/1/2021
1.0.0-preview-1088021240 716 8/1/2021
1.0.0-preview-1083990424 657 7/31/2021
1.0.0-preview-1080710191 637 7/30/2021
1.0.0-preview-1080701269 665 7/30/2021
1.0.0-preview-1079028054 669 7/29/2021
1.0.0-preview-1079000079 666 7/29/2021
1.0.0-preview-1078977564 743 7/29/2021
1.0.0-preview-1069218438 576 7/26/2021
1.0.0-preview-1065692127 705 7/26/2021
1.0.0-preview-1054554829 620 7/22/2021
1.0.0-preview-1054460177 677 7/22/2021
1.0.0-preview-1044919966 663 7/19/2021
1.0.0-preview-1043697034 560 7/19/2021
1.0.0-preview-1001211231 659 7/5/2021
1.0.0-preview-1001204475 652 7/5/2021
0.9.5-preview-243240046 869 9/7/2020
0.9.5-preview-243219862 925 9/7/2020