DiffSharp.Backends.Torch 1.0.0-preview-1222163389

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There is a newer version of this package available.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-1222163389
                    
NuGet\Install-Package DiffSharp.Backends.Torch -Version 1.0.0-preview-1222163389
                    
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-1222163389" />
                    
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-1222163389" />
                    
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-1222163389
                    
#r "nuget: DiffSharp.Backends.Torch, 1.0.0-preview-1222163389"
                    
#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-1222163389
                    
#: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-1222163389&prerelease
                    
Install as a Cake Addin
#tool nuget:?package=DiffSharp.Backends.Torch&version=1.0.0-preview-1222163389&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 6,514 3/26/2022
1.0.7-preview2044360861 617 3/26/2022
1.0.7-preview1873603133 674 2/21/2022
1.0.7-preview1872895008 663 2/20/2022
1.0.7-preview1872194677 668 2/20/2022
1.0.7-preview1867437105 646 2/19/2022
1.0.7-preview1838897476 645 2/14/2022
1.0.7-preview1838869913 649 2/14/2022
1.0.6 6,891 2/9/2022
1.0.6-preview1838805210 647 2/14/2022
1.0.6-preview1838790927 722 2/14/2022
1.0.6-preview1838781533 649 2/14/2022
1.0.6-preview1838761310 678 2/14/2022
1.0.6-preview1838574327 733 2/14/2022
1.0.6-preview1838238393 677 2/13/2022
1.0.6-preview1837967313 709 2/13/2022
1.0.6-preview1837932839 480 2/13/2022
1.0.6-preview1837857091 479 2/13/2022
1.0.5 3,819 2/9/2022
1.0.4 3,990 2/8/2022
1.0.3 5,080 2/8/2022
1.0.2 4,201 2/8/2022
1.0.1 5,048 11/8/2021
1.0.0-preview-987646120 812 6/30/2021
1.0.0-preview-964642900 783 6/23/2021
1.0.0-preview-964597118 607 6/23/2021
1.0.0-preview-964532207 675 6/23/2021
1.0.0-preview-964414624 683 6/23/2021
1.0.0-preview-962665709 533 6/23/2021
1.0.0-preview-961120541 579 6/22/2021
1.0.0-preview-958984202 617 6/22/2021
1.0.0-preview-783523654 760 4/25/2021
1.0.0-preview-783503343 669 4/25/2021
1.0.0-preview-783410550 701 4/25/2021
1.0.0-preview-781810429 645 4/25/2021
1.0.0-preview-775752139 734 4/22/2021
1.0.0-preview-774228953 700 4/22/2021
1.0.0-preview-769092916 683 4/21/2021
1.0.0-preview-768013090 664 4/20/2021
1.0.0-preview-762002995 651 4/19/2021
1.0.0-preview-761040762 716 4/18/2021
1.0.0-preview-761018834 721 4/18/2021
1.0.0-preview-756065403 617 4/16/2021
1.0.0-preview-755638011 648 4/16/2021
1.0.0-preview-752421465 681 4/15/2021
1.0.0-preview-748176085 677 4/14/2021
1.0.0-preview-746203897 654 4/13/2021
1.0.0-preview-746138300 677 4/13/2021
1.0.0-preview-745205599 636 4/13/2021
1.0.0-preview-739671157 663 4/12/2021
1.0.0-preview-712483117 666 4/2/2021
1.0.0-preview-699281085 612 3/29/2021
1.0.0-preview-699125312 668 3/29/2021
1.0.0-preview-698458610 718 3/29/2021
1.0.0-preview-697743517 727 3/29/2021
1.0.0-preview-697665469 663 3/29/2021
1.0.0-preview-690194555 668 3/26/2021
1.0.0-preview-688124591 649 3/25/2021
1.0.0-preview-687886352 645 3/25/2021
1.0.0-preview-681551353 666 3/24/2021
1.0.0-preview-681104545 700 3/23/2021
1.0.0-preview-680643606 736 3/23/2021
1.0.0-preview-679950457 668 3/23/2021
1.0.0-preview-669022451 676 3/19/2021
1.0.0-preview-643151273 571 3/11/2021
1.0.0-preview-633398743 639 3/8/2021
1.0.0-preview-633348953 673 3/8/2021
1.0.0-preview-621803110 713 3/4/2021
1.0.0-preview-611561611 705 3/1/2021
1.0.0-preview-611172961 616 3/1/2021
1.0.0-preview-593196134 586 2/23/2021
1.0.0-preview-589424126 633 2/22/2021
1.0.0-preview-589402583 665 2/22/2021
1.0.0-preview-586837684 618 2/21/2021
1.0.0-preview-586440747 672 2/21/2021
1.0.0-preview-498549439 669 1/20/2021
1.0.0-preview-485581354 710 1/14/2021
1.0.0-preview-392545720 775 11/30/2020
1.0.0-preview-392233243 722 11/30/2020
1.0.0-preview-392187079 793 11/30/2020
1.0.0-preview-390203270 716 11/29/2020
1.0.0-preview-387146713 811 11/27/2020
1.0.0-preview-386097798 846 11/26/2020
1.0.0-preview-385867359 848 11/26/2020
1.0.0-preview-385523380 732 11/26/2020
1.0.0-preview-384128234 839 11/25/2020
1.0.0-preview-374537774 799 11/20/2020
1.0.0-preview-374468367 692 11/20/2020
1.0.0-preview-368681212 758 11/17/2020
1.0.0-preview-368659044 847 11/17/2020
1.0.0-preview-364746088 880 11/15/2020
1.0.0-preview-364706087 812 11/15/2020
1.0.0-preview-363372268 732 11/14/2020
1.0.0-preview-362038354 776 11/13/2020
1.0.0-preview-362004577 765 11/13/2020
1.0.0-preview-361488593 716 11/13/2020
1.0.0-preview-360710530 760 11/13/2020
1.0.0-preview-359756455 749 11/12/2020
1.0.0-preview-358333968 805 11/11/2020
1.0.0-preview-358184921 809 11/11/2020
1.0.0-preview-358174946 775 11/11/2020
1.0.0-preview-349704450 864 11/6/2020
1.0.0-preview-349564717 848 11/6/2020
1.0.0-preview-343634015 861 11/3/2020
1.0.0-preview-343610434 768 11/3/2020
1.0.0-preview-328097867 1,068 10/26/2020
1.0.0-preview-322875134 809 10/22/2020
1.0.0-preview-315311536 751 10/19/2020
1.0.0-preview-309180753 794 10/15/2020
1.0.0-preview-309013019 831 10/15/2020
1.0.0-preview-308920132 739 10/15/2020
1.0.0-preview-308837132 804 10/15/2020
1.0.0-preview-308751690 769 10/15/2020
1.0.0-preview-308593840 782 10/15/2020
1.0.0-preview-299173506 866 10/10/2020
1.0.0-preview-292259854 873 10/6/2020
1.0.0-preview-291985511 819 10/6/2020
1.0.0-preview-291903007 792 10/6/2020
1.0.0-preview-291722399 820 10/6/2020
1.0.0-preview-284981464 767 10/2/2020
1.0.0-preview-284595614 753 10/2/2020
1.0.0-preview-280886714 826 9/30/2020
1.0.0-preview-278989673 769 9/29/2020
1.0.0-preview-277686264 767 9/29/2020
1.0.0-preview-277653295 776 9/29/2020
1.0.0-preview-275730148 838 9/28/2020
1.0.0-preview-275727262 811 9/28/2020
1.0.0-preview-267667710 859 9/22/2020
1.0.0-preview-263264614 867 9/20/2020
1.0.0-preview-263250971 885 9/20/2020
1.0.0-preview-262623253 756 9/19/2020
1.0.0-preview-258339834 797 9/16/2020
1.0.0-preview-258210544 825 9/16/2020
1.0.0-preview-258177528 868 9/16/2020
1.0.0-preview-258119380 870 9/16/2020
1.0.0-preview-256594931 820 9/16/2020
1.0.0-preview-256435175 891 9/15/2020
1.0.0-preview-253816091 791 9/14/2020
1.0.0-preview-253197654 813 9/14/2020
1.0.0-preview-247523274 754 9/10/2020
1.0.0-preview-247118168 838 9/9/2020
1.0.0-preview-246444372 882 9/9/2020
1.0.0-preview-246434361 840 9/9/2020
1.0.0-preview-246402060 762 9/9/2020
1.0.0-preview-245105781 776 9/8/2020
1.0.0-preview-244918410 844 9/8/2020
1.0.0-preview-243478925 760 9/7/2020
1.0.0-preview-243471084 806 9/7/2020
1.0.0-preview-243323135 902 9/7/2020
1.0.0-preview-1413494063 702 11/2/2021
1.0.0-preview-1405354284 639 10/31/2021
1.0.0-preview-1338129467 693 10/13/2021
1.0.0-preview-1327345305 784 10/11/2021
1.0.0-preview-1325686991 630 10/10/2021
1.0.0-preview-1324682939 776 10/10/2021
1.0.0-preview-1239345497 706 9/15/2021
1.0.0-preview-1227879651 684 9/13/2021
1.0.0-preview-1227810778 689 9/13/2021
1.0.0-preview-1222163389 680 9/10/2021
1.0.0-preview-1177844564 726 8/28/2021
1.0.0-preview-1176119659 632 8/28/2021
1.0.0-preview-1176116073 638 8/28/2021
1.0.0-preview-1176112166 609 8/28/2021
1.0.0-preview-1172193368 626 8/26/2021
1.0.0-preview-1168287221 616 8/25/2021
1.0.0-preview-1147185155 704 8/19/2021
1.0.0-preview-1133286135 745 8/15/2021
1.0.0-preview-1118120224 715 8/10/2021
1.0.0-preview-1111420036 629 8/9/2021
1.0.0-preview-1111385512 567 8/9/2021
1.0.0-preview-1111166736 625 8/9/2021
1.0.0-preview-1088380884 653 8/1/2021
1.0.0-preview-1088311063 659 8/1/2021
1.0.0-preview-1088021240 736 8/1/2021
1.0.0-preview-1083990424 675 7/31/2021
1.0.0-preview-1080710191 657 7/30/2021
1.0.0-preview-1080701269 683 7/30/2021
1.0.0-preview-1079028054 685 7/29/2021
1.0.0-preview-1079000079 686 7/29/2021
1.0.0-preview-1078977564 760 7/29/2021
1.0.0-preview-1069218438 596 7/26/2021
1.0.0-preview-1065692127 721 7/26/2021
1.0.0-preview-1054554829 638 7/22/2021
1.0.0-preview-1054460177 691 7/22/2021
1.0.0-preview-1044919966 679 7/19/2021
1.0.0-preview-1043697034 578 7/19/2021
1.0.0-preview-1001211231 677 7/5/2021
1.0.0-preview-1001204475 669 7/5/2021
0.9.5-preview-243240046 890 9/7/2020
0.9.5-preview-243219862 947 9/7/2020