1. 02 11月, 2017 1 次提交
    • Hack auc for dense vector labels (#5274) · cdd1da34
      武毅 提交于
      * refine evaluator op types
      
      * update
      
      * follow comments
      
      * update
      
      * fix v2 mnist case
      
      * fix v2 mnist case
      
      * update
      
      * update
      
      * hack auc evaluator for dense vec
      
      * follow comments
      cdd1da34
  2. 28 8月, 2017 1 次提交
  3. 21 8月, 2017 1 次提交
  4. 13 8月, 2017 1 次提交
  5. 22 2月, 2017 1 次提交
  6. 09 2月, 2017 1 次提交
  7. 02 2月, 2017 1 次提交
  8. 09 12月, 2016 1 次提交
  9. 22 11月, 2016 1 次提交
  10. 12 11月, 2016 1 次提交
  11. 02 11月, 2016 1 次提交
    • Q
      Add job=time in trainer, refine cudnn_conv to reduce gpu memory and speed up training. (#218) · 45c81a41
      qingqing01 提交于
      * Add benchmark for PaddlePaddle, tensorflow and caffe
      
      * ConvProjection to reduce memory for goolenet
      
      * Add unit test for ConvProjection.
      1. unit test in test_LayerGrad.
      2. compare the ConvPorjection and CudnnConvLayer, also compare the concat_layer+img_conv_layer and concat_layer_conv_projection.
      
      * Reduce cudnn_conv memory and add benchmark document.
      1. Use TmpMatrix as the workspace in cudnn_conv to reduce gpu memory. It reduce lots of memory.
      2. Add benchmark document.
      3. fix smallnet_mnist_cifar.py in paddle.
      
      * Add job=time and refine cudnn_conv to reduce gpu memroy and speed up
      
      * Refine cudnn_conv and shared biases operation in concat_layer and mixed_layer.
      
      * follow comments
      
      * follow comments
      
      * Use unique_ptr to prevent memory leaks in CudnnConvLayer.
      45c81a41
  12. 29 8月, 2016 1 次提交