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All Projects → BlinkDL → Blinkdl

BlinkDL / Blinkdl

Licence: apache-2.0
A minimalist deep learning library in Javascript using WebGL + asm.js. Run convolutional neural network in your browser.

Programming Languages

javascript
184084 projects - #8 most used programming language

Labels

deep-learningneural-networkdeep-neural-networksneural-networksdeeplearning

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BlinkDL

A minimalist deep learning library in Javascript using WebGL + asm.js. Runs in your browser.

Currently it is a proof-of-concept (inference only). Note: Convolution is buggy when memories overlap.

The WebGL backend is powered by weblas: https://github.com/waylonflinn/weblas.

Example

https://withablink.coding.me/goPolicyNet/ : a weiqi (baduk, go) policy network in AlphaGo style:

board_image 
const N = 19;
const NN = N * N;
const nFeaturePlane = 8;
const nFilter = 128;

const x = new BlinkArray();
x.Init('weblas');
x.nChannel = nFeaturePlane;
x.data = new Float32Array(nFeaturePlane * NN);
for (var i = 0; i < NN; i++)
    x.data[5 * NN + i] = 1; // set feature plane for empty board

// pre-act residual network with 6 residual blocks
const bak = new Float32Array(nFilter * NN);
x.Convolution(nFilter, 3);
x.CopyTo(bak);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.Add(bak).CopyTo(bak);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.Add(bak).CopyTo(bak);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.Add(bak).CopyTo(bak);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.Add(bak).CopyTo(bak);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.Add(bak).CopyTo(bak);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.BatchNorm().ReLU().Convolution(nFilter, 3);
x.Add(bak);
x.BatchNorm().ReLU().Convolution(1, 1).Softmax();
performance_image

Usage

<script src='weblas.js' type='text/javascript'></script>
<script src='BlinkDL.js' type='text/javascript'></script>

Todo

  • [x] Convolution (3x3_pad_1 and 1x1), BatchNorm, ReLU, Softmax
  • [ ] Pooling layer
  • [ ] FC layer
  • [ ] Strided convolution
  • [ ] Transposed convolution
  • [ ] Webworker and async
  • [ ] Faster inference with weblas pipeline, WebGPU, WebAssembly
  • [ ] Memory manager
  • [ ] Training
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