内容简介：Implementation of the estimation of model size and flop counts for convolutional neural networks with MXNET-Scala.For now, the estimation of flops only consider Layers: Convolution, Deconvolution, FullyConnected, Pooling, relu
MXNET-Scala Useful Tools
Implementation of the estimation of model size and flop counts for convolutional neural networks with MXNET-Scala.
https://github.com/albanie/convnet-burden
For now, the estimation of flops only consider Layers: Convolution, Deconvolution, FullyConnected, Pooling, relu
Building
Tested on Ubuntu 14.04
Requirements
- sbt 0.13
- Mxnet
steps
1, compile Mxnet with CUDA, then compile the scala-pkg;
2,
cd Mxnet-Scala/UsefulTools mkdir lib
3, copy your compiled mxnet-full_2.11-linux-x86_64-gpu-1.3.1-SNAPSHOT.jar
into lib folder;
4, run sbt, compile the project
Running
run cal_flops.sh
under scripts folder
caffenet flops: 723.0072 MFLOPS model size: 232.56387 MB squeezenet1-0 flops: 861.60394 MFLOPS model size: 4.7623596 MB resnet-101 flops: 7818.2407 MFLOPS model size: 170.28586 MB resnext-101-64x4d flops: 15491.882 MFLOPS model size: 319.13058 MB
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