* "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

* Adding nesterov momentum to python momentum wrapper
* Fixing optimizer test after merge

* Extract apply_backward_pass to backward.py

Rename apply_backward_pass to append_backward_ops

* Fix CI

* Update design doc

* Adding Adam Python wrapper

* Adding tests for Python Adam wrapper

* Adding the interface for the momentum optimizer
* Adding a comment about accumulators

* init parameter base class

* optimize the Comments of optimizer

* basic implimentation of optimizer

* add test_optimizer

* add no_grad_set to interface

* update optimizer.py

* python code can run

* fix some problem

* add sync_with_cpp to Python Program and Block

* sync vars and ops in block from cpp

* optimize code and add some comment

* add more check for sync

* update optimizer with return value of Backward

* rm unused code

* infer shape when create gradient vairiable

* update test_optimizer

* update test_program.py

* update backward test

* follow comment