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Open-source Deep Learning library in C# with CUDA and BLAS support
C# Cuda
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SharpNet is an Open-source Deep Learning library written in C# 7.0.

It supports:

  • Residual Networks v1, v2 and WideResNet
  • DenseNet
  • Dropout / BatchNorm / Conv / Pooling / Dense / Concatenate / Shortcut layers
  • Elu / Relu / Sigmoid / Softmax activations
  • SGD & Adam optimizers
  • Image Data Augmentation (with Cutout/CutMix/Mixup)
  • Ensemble Learning

It can be run both on GPU (using NVIDIA cuDNN) and on the CPU (using MKL Blas).

It is targeted to make a good use of the GPU (even if it is not currently as fast as MxNet) :

  • on ResNet18 v1, it is between 1.5x (batch size = 128) and 3x time (batch size = 32) faster then TensorFlow

It requires:

Next Targets:

  • Add ResNet v2 support => DONE
  • Add Dense Network support => DONE
  • Cutout => DONE
  • Add CutMix => DONE
  • Add Mixup => DONE
  • Add multi GPU support
  • Add RNN / LSTM support
  • Improve memory efficiency for gradients => DONE
  • Add Wide ResNet / Wide DenseNet support => DONE
  • Improve Image Data Augmentation (with rotation) => DONE
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