DiffSharp.Backends.Torch 1.0.0-preview-961120541

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There is a newer version of this package available.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-961120541
                    
NuGet\Install-Package DiffSharp.Backends.Torch -Version 1.0.0-preview-961120541
                    
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-961120541" />
                    
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-961120541" />
                    
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-961120541
                    
#r "nuget: DiffSharp.Backends.Torch, 1.0.0-preview-961120541"
                    
#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-961120541
                    
#: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-961120541&prerelease
                    
Install as a Cake Addin
#tool nuget:?package=DiffSharp.Backends.Torch&version=1.0.0-preview-961120541&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 6,107 3/26/2022
1.0.7-preview2044360861 465 3/26/2022
1.0.7-preview1873603133 509 2/21/2022
1.0.7-preview1872895008 498 2/20/2022
1.0.7-preview1872194677 486 2/20/2022
1.0.7-preview1867437105 463 2/19/2022
1.0.7-preview1838897476 505 2/14/2022
1.0.7-preview1838869913 479 2/14/2022
1.0.6 6,728 2/9/2022
1.0.6-preview1838805210 488 2/14/2022
1.0.6-preview1838790927 565 2/14/2022
1.0.6-preview1838781533 512 2/14/2022
1.0.6-preview1838761310 474 2/14/2022
1.0.6-preview1838574327 554 2/14/2022
1.0.6-preview1838238393 508 2/13/2022
1.0.6-preview1837967313 533 2/13/2022
1.0.6-preview1837932839 356 2/13/2022
1.0.6-preview1837857091 352 2/13/2022
1.0.5 3,691 2/9/2022
1.0.4 3,841 2/8/2022
1.0.3 4,946 2/8/2022
1.0.2 4,064 2/8/2022
1.0.1 4,910 11/8/2021
1.0.0-preview-987646120 664 6/30/2021
1.0.0-preview-964642900 623 6/23/2021
1.0.0-preview-964597118 485 6/23/2021
1.0.0-preview-964532207 544 6/23/2021
1.0.0-preview-964414624 552 6/23/2021
1.0.0-preview-962665709 410 6/23/2021
1.0.0-preview-961120541 454 6/22/2021
1.0.0-preview-958984202 489 6/22/2021
1.0.0-preview-783523654 630 4/25/2021
1.0.0-preview-783503343 530 4/25/2021
1.0.0-preview-783410550 559 4/25/2021
1.0.0-preview-781810429 504 4/25/2021
1.0.0-preview-775752139 591 4/22/2021
1.0.0-preview-774228953 543 4/22/2021
1.0.0-preview-769092916 558 4/21/2021
1.0.0-preview-768013090 531 4/20/2021
1.0.0-preview-762002995 505 4/19/2021
1.0.0-preview-761040762 566 4/18/2021
1.0.0-preview-761018834 594 4/18/2021
1.0.0-preview-756065403 506 4/16/2021
1.0.0-preview-755638011 506 4/16/2021
1.0.0-preview-752421465 535 4/15/2021
1.0.0-preview-748176085 522 4/14/2021
1.0.0-preview-746203897 509 4/13/2021
1.0.0-preview-746138300 542 4/13/2021
1.0.0-preview-745205599 486 4/13/2021
1.0.0-preview-739671157 517 4/12/2021
1.0.0-preview-712483117 525 4/2/2021
1.0.0-preview-699281085 466 3/29/2021
1.0.0-preview-699125312 520 3/29/2021
1.0.0-preview-698458610 567 3/29/2021
1.0.0-preview-697743517 587 3/29/2021
1.0.0-preview-697665469 525 3/29/2021
1.0.0-preview-690194555 530 3/26/2021
1.0.0-preview-688124591 496 3/25/2021
1.0.0-preview-687886352 499 3/25/2021
1.0.0-preview-681551353 538 3/24/2021
1.0.0-preview-681104545 545 3/23/2021
1.0.0-preview-680643606 572 3/23/2021
1.0.0-preview-679950457 524 3/23/2021
1.0.0-preview-669022451 530 3/19/2021
1.0.0-preview-643151273 431 3/11/2021
1.0.0-preview-633398743 508 3/8/2021
1.0.0-preview-633348953 509 3/8/2021
1.0.0-preview-621803110 573 3/4/2021
1.0.0-preview-611561611 557 3/1/2021
1.0.0-preview-611172961 478 3/1/2021
1.0.0-preview-593196134 452 2/23/2021
1.0.0-preview-589424126 505 2/22/2021
1.0.0-preview-589402583 535 2/22/2021
1.0.0-preview-586837684 480 2/21/2021
1.0.0-preview-586440747 528 2/21/2021
1.0.0-preview-498549439 550 1/20/2021
1.0.0-preview-485581354 550 1/14/2021
1.0.0-preview-392545720 630 11/30/2020
1.0.0-preview-392233243 591 11/30/2020
1.0.0-preview-392187079 633 11/30/2020
1.0.0-preview-390203270 572 11/29/2020
1.0.0-preview-387146713 652 11/27/2020
1.0.0-preview-386097798 688 11/26/2020
1.0.0-preview-385867359 691 11/26/2020
1.0.0-preview-385523380 576 11/26/2020
1.0.0-preview-384128234 672 11/25/2020
1.0.0-preview-374537774 638 11/20/2020
1.0.0-preview-374468367 567 11/20/2020
1.0.0-preview-368681212 614 11/17/2020
1.0.0-preview-368659044 688 11/17/2020
1.0.0-preview-364746088 701 11/15/2020
1.0.0-preview-364706087 654 11/15/2020
1.0.0-preview-363372268 584 11/14/2020
1.0.0-preview-362038354 605 11/13/2020
1.0.0-preview-362004577 621 11/13/2020
1.0.0-preview-361488593 557 11/13/2020
1.0.0-preview-360710530 614 11/13/2020
1.0.0-preview-359756455 619 11/12/2020
1.0.0-preview-358333968 640 11/11/2020
1.0.0-preview-358184921 651 11/11/2020
1.0.0-preview-358174946 621 11/11/2020
1.0.0-preview-349704450 715 11/6/2020
1.0.0-preview-349564717 696 11/6/2020
1.0.0-preview-343634015 698 11/3/2020
1.0.0-preview-343610434 628 11/3/2020
1.0.0-preview-328097867 905 10/26/2020
1.0.0-preview-322875134 651 10/22/2020
1.0.0-preview-315311536 595 10/19/2020
1.0.0-preview-309180753 630 10/15/2020
1.0.0-preview-309013019 688 10/15/2020
1.0.0-preview-308920132 607 10/15/2020
1.0.0-preview-308837132 642 10/15/2020
1.0.0-preview-308751690 645 10/15/2020
1.0.0-preview-308593840 651 10/15/2020
1.0.0-preview-299173506 727 10/10/2020
1.0.0-preview-292259854 724 10/6/2020
1.0.0-preview-291985511 679 10/6/2020
1.0.0-preview-291903007 628 10/6/2020
1.0.0-preview-291722399 690 10/6/2020
1.0.0-preview-284981464 640 10/2/2020
1.0.0-preview-284595614 610 10/2/2020
1.0.0-preview-280886714 690 9/30/2020
1.0.0-preview-278989673 638 9/29/2020
1.0.0-preview-277686264 619 9/29/2020
1.0.0-preview-277653295 645 9/29/2020
1.0.0-preview-275730148 701 9/28/2020
1.0.0-preview-275727262 671 9/28/2020
1.0.0-preview-267667710 701 9/22/2020
1.0.0-preview-263264614 732 9/20/2020
1.0.0-preview-263250971 764 9/20/2020
1.0.0-preview-262623253 620 9/19/2020
1.0.0-preview-258339834 648 9/16/2020
1.0.0-preview-258210544 688 9/16/2020
1.0.0-preview-258177528 732 9/16/2020
1.0.0-preview-258119380 725 9/16/2020
1.0.0-preview-256594931 686 9/16/2020
1.0.0-preview-256435175 734 9/15/2020
1.0.0-preview-253816091 638 9/14/2020
1.0.0-preview-253197654 659 9/14/2020
1.0.0-preview-247523274 611 9/10/2020
1.0.0-preview-247118168 686 9/9/2020
1.0.0-preview-246444372 742 9/9/2020
1.0.0-preview-246434361 717 9/9/2020
1.0.0-preview-246402060 592 9/9/2020
1.0.0-preview-245105781 621 9/8/2020
1.0.0-preview-244918410 675 9/8/2020
1.0.0-preview-243478925 619 9/7/2020
1.0.0-preview-243471084 636 9/7/2020
1.0.0-preview-243323135 746 9/7/2020
1.0.0-preview-1413494063 557 11/2/2021
1.0.0-preview-1405354284 511 10/31/2021
1.0.0-preview-1338129467 554 10/13/2021
1.0.0-preview-1327345305 649 10/11/2021
1.0.0-preview-1325686991 498 10/10/2021
1.0.0-preview-1324682939 654 10/10/2021
1.0.0-preview-1239345497 567 9/15/2021
1.0.0-preview-1227879651 562 9/13/2021
1.0.0-preview-1227810778 564 9/13/2021
1.0.0-preview-1222163389 548 9/10/2021
1.0.0-preview-1177844564 575 8/28/2021
1.0.0-preview-1176119659 483 8/28/2021
1.0.0-preview-1176116073 503 8/28/2021
1.0.0-preview-1176112166 466 8/28/2021
1.0.0-preview-1172193368 496 8/26/2021
1.0.0-preview-1168287221 483 8/25/2021
1.0.0-preview-1147185155 565 8/19/2021
1.0.0-preview-1133286135 604 8/15/2021
1.0.0-preview-1118120224 584 8/10/2021
1.0.0-preview-1111420036 497 8/9/2021
1.0.0-preview-1111385512 429 8/9/2021
1.0.0-preview-1111166736 495 8/9/2021
1.0.0-preview-1088380884 517 8/1/2021
1.0.0-preview-1088311063 523 8/1/2021
1.0.0-preview-1088021240 595 8/1/2021
1.0.0-preview-1083990424 546 7/31/2021
1.0.0-preview-1080710191 511 7/30/2021
1.0.0-preview-1080701269 539 7/30/2021
1.0.0-preview-1079028054 544 7/29/2021
1.0.0-preview-1079000079 540 7/29/2021
1.0.0-preview-1078977564 599 7/29/2021
1.0.0-preview-1069218438 453 7/26/2021
1.0.0-preview-1065692127 598 7/26/2021
1.0.0-preview-1054554829 500 7/22/2021
1.0.0-preview-1054460177 560 7/22/2021
1.0.0-preview-1044919966 521 7/19/2021
1.0.0-preview-1043697034 453 7/19/2021
1.0.0-preview-1001211231 547 7/5/2021
1.0.0-preview-1001204475 516 7/5/2021
0.9.5-preview-243240046 753 9/7/2020
0.9.5-preview-243219862 777 9/7/2020