SiaNet 0.3.0

.NET Framework
There is a newer version of this package available.
See the version list below for details.
Install-Package SiaNet -Version 0.3.0
dotnet add package SiaNet --version 0.3.0
<PackageReference Include="SiaNet" Version="0.3.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add SiaNet --version 0.3.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: SiaNet, 0.3.0"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install SiaNet as a Cake Addin
#addin nuget:?package=SiaNet&version=0.3.0

// Install SiaNet as a Cake Tool
#tool nuget:?package=SiaNet&version=0.3.0
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Build Status Join the chat at https://gitter.im/sia-cog/SiaNet

A C# deep learning wrapper with CNTK backend

Developing a C# wrapper to help developer easily create and train deep neural network models. I am working on enhancing the interface to load data, build model, train and predict.

Install using NuGet

GPU and CPU Version: https://www.nuget.org/packages/SiaNet

For better performance on CPU please use CPU only version. CPU Only Version: https://www.nuget.org/packages/SiaNet.CPUOnly/

Load dataset (Housing regression example)

DataFrame frame = new DataFrame();

frame.LoadFromCsv(trainFile);

var xy = frame.SplitXY(14, new[] { 1, 13 });

traintest = xy.SplitTrainTest(0.25);

Load Sample Dataset (MNIST)

Downloader.DownloadSample(SampleDataset.MNIST);

var samplePath = Downloader.GetSamplePath(SampleDataset.MNIST);

train = ImageDataGenerator.FlowFromText(samplePath.Train);

validation = ImageDataGenerator.FlowFromText(samplePath.Test);

Build Model

model = new Sequential();

model.Add(new Dense(13, 12, OptActivations.ReLU));

model.Add(new Dense(13, OptActivations.ReLU));

model.Add(new Dense(1));

Build Convolution Layers

model.Add(new Conv2D(Tuple.Create(imageDim[0], imageDim[1], imageDim[2]), 4, Tuple.Create(3, 3), Tuple.Create(2, 2), activation: OptActivations.None, weightInitializer: OptInitializers.Xavier, useBias: true, biasInitializer: OptInitializers.Ones));

model.Add(new MaxPool2D(Tuple.Create(3, 3)));

model.Add(new Conv2D(8, Tuple.Create(3, 3), Tuple.Create(2, 2), activation: OptActivations.None, weightInitializer: OptInitializers.Xavier));

model.Add(new MaxPool2D(Tuple.Create(3, 3)));

model.Add(new Dense(numClasses));

Configure Training callbacks

model.OnEpochEnd += Model_OnEpochEnd;

model.OnTrainingEnd += Model_OnTrainingEnd;

model.OnBatchEnd += Model_OnBatchEnd;

Train Model

model.Compile(OptOptimizers.Adam, OptLosses.MeanSquaredError, OptMetrics.MAE, Regulizers.RegL2(0.1)); model.Train(traintest.Train, 64, 200, traintest.Test);

API Documentation: https://deepakkumar1984.github.io/SiaNet/

Examples Docs (More to add)

Product Versions
.NET Framework net
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Version Downloads Last updated
0.4.2.67 880 3/25/2019
0.4.1.65 402 3/21/2019
0.4.1.64 403 3/18/2019
0.4.1.38 406 3/13/2019
0.4.1.31 439 3/4/2019
0.3.0 962 11/29/2017
0.2.2.2 696 11/11/2017

- Implemented LSTM layer
- Bug Fixes
- More examples