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The project changed name for clarity. See

dotnet add package Gradient --version                
NuGet\Install-Package Gradient -Version                
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="Gradient" Version="" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Gradient --version                
#r "nuget: Gradient,"                
#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.
// Install Gradient as a Cake Addin
#addin nuget:?package=Gradient&version=

// Install Gradient as a Cake Tool
#tool nuget:?package=Gradient&version=                

FULL TensorFlow 1.15 for .NET with Keras. Build, train, checkpoint, execute models.

Comparison with TensorFlowSharp:
Comparison with TensorFlow.NET:

Allows building arbitrary machine learning models, training them, and loading and executing pre-trained models using the most popular machine learning framework out there: TensorFlow. All from your favorite comfy .NET language. Supports both CPU and GPU training (the later requires CUDA or a special build of TensorFlow).

Provides access to full tf.keras and tf.contrib APIs, including estimators.

This preview will expire.


This version requires Python 3.x x64 to be installed with tensorflow or tensorflow-gpu 1.15. See the official installation instructions in (ensure you are installing version 1.15 to avoid hard-to-debug issues).

Please, report any issues to
For community support use with tags (must be all 3 together) tensorflow, gradient, and .net.
For on-site/remote support for this preview email .

More information in NuGet package release notes and at the project web page: .

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  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. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

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Version Downloads Last updated 2,730 2/11/2020
0.1.10-tech-preview6.4 598 10/11/2019
0.1.10-tech-preview6.2 471 10/1/2019
0.1.10-tech-preview5.1.1 485 5/21/2019
0.1.10-tech-preview5 800 3/4/2019
0.1.10-tech-preview4 814 2/15/2019

This version requires Python 3.x x64 to be installed with tensorflow or tensorflow-gpu. See the official installation instructions in (ensure you are installing version 1.15 to avoid hard-to-debug issues).

If your app, that uses Gradient, targets net4xx (like net472), you need to specify a proper runtime identifier to run and publish. e.g. "dotnet publish -r win" and "dotnet run -r win7-x64". Note, "run" requires specific identifier.

What's new

Preview 7:
- TensorFlow 1.15
- strongly-typed accessors for ndarray<T>
- arithmetic, bitwise and comparison operators on Tensors (note, now to check for null `is null` must be used instead of `== null`)
- StartUsing extension on classes like Session, variable_scope, etc to allow simpler `using` blocks in .NET
- improved support for enums
- prepackaged TensorFlow runtime in a NuGet package for easy installation (separate): LostTech.TensorFlow.Python
- minimal wrapper for NumPy is released in a separate package (see dependencies)
- runtime initialization moved to Gradient.Runtime
- bugfixes: + internally reported bugs
- new sample: reinforcement learning with Unity ML agents (see after 2020/02/10)

Preview 6:
- feature: enabled inheriting from TensorFlow classes. Now it is possible to build custom Keras layers, callbacks, etc
- feature: automatic marshalling of Gradient types for use with TensorFlow
- fixed an ability to modify collections belonging to TensorFlow objects
- fixed crash when enumerating TensorFlow collections without an explicit lock
- preview 6 will expire in March 2020

Preview 5.1:
- improved passing dictionaries
- setup: optionally specify Conda environment via an environment variable
- setup: fixed Conda environment autodectection on Linux
- improved argument types in many places
- Gradient warnings are now printed to Console.Error by default, instead of Console.Out
- fixed crashes on dynamic interop and multithreaded enumeration
- fixed some properties not being exposed
- preview 5.1 will expire in Oct 2019

Preview 5:
- support for indexing Tensor objects via `dynamic`
- allow using specific Python environment via GradientSetup.UsePythonEnvironment

Preview 4:
- support for Ubuntu 18.04 x64 and MacOS with .NET Core; other *nix OS might work too

Preview 2:
- dynamically typed overloads, that enable fallback for tricky signatures
- a common interface for tf.Variable and tf.Tensor
- enabled enumeration over TensorFlow collection types