* 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.
* Because in cluster maybe use a lot machine to train a model, and some parameter size could be too small for ParameterServer. Then some of pservers could not have any ParamBlock.
* Also, because ports_num or ports_num_for_sparse is too large, then give a warning in runtime.
* fix interface bug of block_expand_layer and add unittest
* auto compute num_channels
* default value of num_channels is None
* adjust input order of block_expand
* add input sparse data check for sparse layer at runtime,
to avoid invalid data access at pserver end while doing prefetch
* remote sparse design support binary sparse and float saprse both
* Fix sparse training for trainer_count=1
For trainer_count=1, the gradient machine is NeuralNetwork, which does not create parameter buf for PARAMETER_GRADIENT for sparse update in Parameter::enableType. But gradient parameter buf is still used in SgdThreadUpdater.
* Minor update to comment
* fix DataProvider create function args bug
Change-Id: I9e3a1c535c805bf30204a14aea8d5143ff534784
* remove PserverForPython.h which is not used
Change-Id: I2b27f1f3c11a42766a92fc689f0f5f1f73ee1d70
* add internal document script
Change-Id: Ia0fec79456caea0b271f9903cc13e8a3d32e0774
* support rectangle padding, stride, window and input for PoolProjection
* Follow comments.
1. Remove start
2. refine img_pool_a/b.conf for test_NetworkCompare
3. Split unit test
* Modify the test in img_layers.py
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