- 25 7月, 2017 1 次提交
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由 wanghaoshuang 提交于
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- 21 3月, 2017 3 次提交
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由 wangyang59 提交于
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由 wangyang59 提交于
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由 wangyang59 提交于
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- 27 12月, 2016 1 次提交
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由 liaogang 提交于
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- 16 12月, 2016 3 次提交
- 15 12月, 2016 1 次提交
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由 xuwei06 提交于
Make sure the input size is correct. Change-Id: I2559075e32a098c5ed51942ff8351d964a6d6c75
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- 12 12月, 2016 1 次提交
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由 Yu Yang 提交于
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- 09 12月, 2016 1 次提交
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由 Yi Wang 提交于
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- 01 12月, 2016 1 次提交
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由 wangyang59 提交于
Added a test in test_NetworkCompare to verify cudnn and exconv, fixed a bug in cudnn_conv in dealing with groups
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- 22 11月, 2016 1 次提交
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由 Luo Tao 提交于
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- 17 11月, 2016 1 次提交
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由 Luo Tao 提交于
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- 02 11月, 2016 1 次提交
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由 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.
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