SiaNet 0.3.0
See the version list below for details.
dotnet add package SiaNet --version 0.3.0
NuGet\Install-Package SiaNet -Version 0.3.0
<PackageReference Include="SiaNet" Version="0.3.0" />
paket add SiaNet --version 0.3.0
#r "nuget: SiaNet, 0.3.0"
// 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
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)
- XOR Example (Build dataset): https://github.com/deepakkumar1984/SiaNet/wiki/Example-Build-Dataset---XOR-Gate
- Housing Regression: https://github.com/deepakkumar1984/SiaNet/wiki/Example---Housing-Regression-Problem
- MNIST Training: https://github.com/deepakkumar1984/SiaNet/wiki/Example---MNIST-Training
- Image Classification: https://github.com/deepakkumar1984/SiaNet/wiki/Example---Image-Classification
- Object Detection: https://github.com/deepakkumar1984/SiaNet/wiki/Example---Object-Detection
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET Framework | net is compatible. |
-
- CNTK.GPU (>= 2.2.0)
- EMGU.CV (>= 3.3.0.2824)
- Newtonsoft.Json (>= 10.0.3)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.
- Implemented LSTM layer
- Bug Fixes
- More examples