out = w * input
where w is a parameter of size 1

Change-Id: Ife682d62323ceb1a20cbbf6269421b20a862d888

Making '*' support the multiplication between a scalar and LayerOutput

Also changing '+' to support adding between a vector and a scalar.

Change-Id: I7daf35590dc2b2f855a29d9ef43ac57979442e0f

Update cluster_train.md for easier understanding

Currently, Paddle on Mac OS X is not deliberate testing through the different versions of  Mac OS X and Clang.
When all these things that we've done, we will reopen Mac build docs.

And rebase

Change-Id: I7ea234b3aa8fc70675af15d91db08242c43fb5ff

* Add elementwise math operations
This allows use to use expressions like: y=log(1+exp(x))
Also added unittests for ActivationFunction
* Enforce keyword arguments for non-positional arguments
* Add LogActivation to doc

* 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.

* DYLD_LIBRARY_PATH is disable after Mac OS X 10.11
* fix clang + gpu compile error on Mac OS
* fix some words and errors in build docs

* Change contribute to paddle to fit new branching model

* add maxout layer, including interface and unittest

* follow maxout comments

* auto setting channels

* fix unittest bug in test_RecurrentGradientMachine

* fix error in doc of quick_start
* There are some warning when execute preprocess.sh 

* Follow #223
* Fix #222

* hierarchical rnn document, add new config example

* update inputs_type of label

* add check for unsupported config

* refine hierarchical document

* refine doc title

* update docs, fix paddle to PaddlePaddle

* follow comments

* add interface and unittest for nce layer

* follow comments

* Rerange Build docs & emphasize them in README.md

* Rerange Build docs & emphasize them in README.md

* Add automatic check AVX in CMake

* Add indent in FindAVX.cmake

* Revise table format and some words in build docs

* Update build docs

* Update build docs

* Add automatic check AVX in CMake

* Add indent in FindAVX.cmake

* Revise table format and some words in build docs

* Update build docs

* Add automatic check AVX in CMake
* Revise table format and some words in build docs

* follow comments to fix bugs

* refine sparse momentum api and unittest
* fix unittests bug

* fix bug in dotmul_operator's api and anotation
* update rnn document
* remove redundant info of projection and operator in layers.py

* min_pool_size would be infinite by default.
  * add unittest for min_pool_size
* Fix bug in can_over_batch_size
  * add unittest for can_over_batch_size
* Add DEFINE_PROVIDER_EX
* Add default value of should_shuffle
  * When training, the default value of should_shuffle is True.
  * When testing, the default value of should_shuffle is False.
  * User a set a provider should_shuffle or not by pass it to `@provider`
  * should_shuffle can handle a list of value, not just boolean
* Add input order mapping by using name
  * Add unittest
* Add check to check input format.
  * Default is close for speed reason.
  * User could stop train when check error, or continue train without
    this train sample.
* use deque instead of vector in generators pool, make erase
  generator faster.
* Add chinese/english documentation
* Make should shuffle = false in unittest
* Add python files to depends.

* Add some comments for CTC layer and fix CTC evalutors, also add interface test

Change cos_sim to use CosSimLayer layer when size=1 and rename convex_comb_layer to linear_comb_layer

Also add an unittest for layers.py, currently for a few things. More need to be added later.