Memory-efficient Implementation of DenseNets
Memory-efficient Implementation of DenseNets 改進densenet模型佔用顯存較大的問題。 對於特徵的極致利用可以提高模型的表現能力，用時由於生成大量的intermediate feature(中間特徵)，因此存儲這些intermediate feature會佔用大量的顯存。爲了能夠在GPU下跑更深的densenet網絡，這篇文章通過對中間特徵採用共享存
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相關文章
- 1. Memory-Efficient Implementation of DenseNets
- 2. 每天一天論文 364/365 Memory-Efficient Implementation of DenseNets
- 3. Implementation of Message Receiver
- 4. Implementation of Kernel Timers
- 5. The Implementation of Rotating Numbers
- 6. DenseNets
- 7. The Implementation of baseline algorithms of Machine Learning
- 8. Algorithm: The implementation of Trie Tree (C++)
- 9. Implementation Model Editor of AVEVA in OpenSceneGraph
- 10. [轉]An overview of Openvswitch implementation