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caffe源码阅读笔记

License: Apache License 2.0

CMake 1.19% Makefile 0.27% Dockerfile 0.03% HTML 0.08% CSS 0.10% Jupyter Notebook 57.68% C++ 33.46% Shell 0.30% Python 4.08% Cuda 2.44% MATLAB 0.37%
caffe deep-learning deeplearning-framework frameworks

caffe-notes's Introduction

Caffe Notes

Caffe源码学习笔记。

虽然Caffe已经是非常古老的框架了,但可从中学习到怎么样从一个网络定义变成一个实际的计算图。

在开发一个迷你的计算图执行引擎时,caffe是一个很好的参考,它的组织结构相比Pytorch、Tensorflow等框架足够简洁、清晰,很适合入门框架开发者学习。

同时,它有足够充分的基础算子,可以帮助我们迅速窥探到OP的内在,包括如何使用cudnn、cublas等高层库、如何手写OP等等。

Abstract

Caffe的核心组件包含五个部分:blobs、layers、nets、solver,以及protobuf。学习过程首先围绕这五个部分的定义和实现展开,再从运行时来看推理和训练过程,以及经典算子的实现。

File Structure

  • caffe:源码注释;
  • notes:笔记;

Todo Progress

  • 0. 总体架构
  • 1. Blob、SyncedMemory分析
  • 2. Layer分析
  • 3. Net分析
  • 4. Solver分析
  • 5. Proto分析
  • 6. 从头到尾的推理过程
  • 7. 从头到尾的训练过程
  • 8. 算子实现

如果发现错误,请及时提出Issue。

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