Add PrecisionRecall Op

* "add sequence conv layer"

* "add book recommender_system testing"

* "add training loop"

* "add sequence layer"

* "add recommender system training data"

* "fix conv2d layer bug"

* add sequence_conv_pool

* "fix input is Null"

* add networks

* "fix based comment"

* "add sum op layer"

* "merge layers"

* Update layers.py

* "fix input is NULL bug"

* "debug embedding table"

* "modify layers.py"

* "fix pool interface"

* "add export type to layers"

* "fix based on comment"

* "need lod info support in all operator"

* "remove accuracy layer"

* "tuning learning rate"

* "add sparse test"

* "add gpu test"

* Update test_recommender_system.py

* optimizer use init_program

* create persistable variable

* add create_persistable_var to block

* optimizer use create_persistable_var

* fix prefix

* move create_global_persistable_var from Block to LayerHelper

* Polish Optimizer initialization code.

* Using the LayerHelper to create initialize operator and variables

* add_accumulator should use an independent data type

* default use param data type for accumulator

* Fix bug

* update

update benchmark data on VGG19

refine mkldnn unit test

Add the LinearChainCrf operator.

* Add documentation of cross-compiling for iOS.

* Correst the typo in documentation of cross-compiling for raspberry pi.

* Set ANDROID_API to 21 when it is specified < 21 for arm64-v8a in build_android.sh.

* Check the input and print the usage in MergeModel.cpp.

Add backward implementation for LSTM operator. 

Allocate aligned memory by posix_memalign.

* "replace enum with string"

* "fix layers"

Set gradient's data type based on its forward variable

* Init commit

* Make executor use ProgramDescBind

* Change Attribute from BlockDesc to BlockDescBind

* Since we will get the program desc in RNN, just BlockDesc is not
  enough.

* add shareLod

* fix sequence_conv grad infershape

1. Change some `auto` to `auto*`
2. Change `Tensor` to `LoDTensor`

* AddBiasOp does not care num_flatten_dims

* Add comments

* "modify layers.py"

* "fix pool interface"

* "add export type to layers"

* "fix based on comment"

correct the index of cluster_train_cn/en.md

Use posix_memalign to allocate aligned memory, since some SIMD instructions require the alignment of memory accesses.

add test_Expand and simply the gserver/tests/CMakeLists