1. Add attr 'average' into ParamAttr.
2. Make 'params_grads' optional for AverageModel.
3. Add option 'average_mean' and 'average_variance' for batch_normal.

* Add RMSProp optimizer warpper.

* Follow comments.

1. Implement 'with model_average.apply()' syntax
2. Init apply_program and restore_program in __init__ functin of ModelAverage

* Add reset and guard to unique_name

* add basic interface for learning rate decay
* add exponential_decay
* add natural_exp_decay
* add inverse_time_decay

* "fix decode bug"

* "follow commnet"

* "fix error"

* "fix hook bug"

* fix based comment

* fix copyright

* fix based on comment

* add copyright hook

* add copyright hook

* refine copyright hook

* "test copyright hook"

* fix check style

* fix ci

* Support Clip in param_attr

* Fix the order of clip & regular

Regular is not need to be clipped

* Simplize system_allocator and fix GPU_INFO

* Remove main_program/startup_program

* Fix optimizer

* Fix CI

* Follow comments

* "add global regularization"

* Polish `append_regularization_ops`

* Add DataFeeder

A v2 API like data feeder for book demos.
We can feed data directly from reader.

* Fix CI

* Add an unittest for while/rnn op forward

* Add unittest for raw while op backward

* Fix CI

Change books just use `import fluid`, not submodules

* Change all `data_type` in Python to `dtype`

* Change `date_type` in C++ to `dtype`

* Refine

* init label_semantic_roles.py

* add linear_chain_crf and test

* complete test_linear_chain_crf

* correct last layer of db_lstm

* update optimizer and initializer

* update param_initializer of embedding_layer

* support load pre trained embedding

* rm unused parameter

* optimize code

* clean code

* fix test

* add todo

* add decayed adagrad python code

* fix typo and order

* small fix

* init commit

* change some dir name

* create learning rate variable for every parameter

* fix ci

* set parameter lr relatively to global lr

* Fix attribute naming for momentum_op

* Fix minor typo in comment

* Fix attribute name

* Fix names in test_optimizer

* Fix python wrapper

* 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

* Adding the increment op for global step

* Changing list to single op as per code review feedback

* Add regularizer code
* Fix code