* Correctly handling multiple inputs and integer inputs for recurrent_group

* Fix ScatterAgentLayer for generation

* Revert sequence_(nest)_rnn.conf

* Add `device` parameter to ExtraAttr in trainer_config_helpers.
* add unittest for it.

* add type compatible check for ParamAttr

Local training with "sparse_update = True" parameter triggers kSgdSparseCpuTraining mode, fix bugs under it.

fix cudnn conv bug which occurs in image classfication demo in GTX GPU

* Also refine unittest to multiple iteration to prevent luckily random number.

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

* remove unnecessary field set in ParameterConfig, Evaluators, etc

update beam_search and seqToseq config, and add ExpActivation api

* split dotmul_projection and dotmul_operator
* bug fix in outputsize checking for mixed layer

* 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 findZLIB in cmake

* Also fix a bug, we should link -ldl at last

Fix signed/unsigned comparison for gcc 4.9

Further fix for memory of RecurrentGradientMachine

Sequences should be sorted according to the number of subsequences they have.

Sequences should be sorted according to the number of subsequences they have.

* try to fix bug for ctc_error_evaluator

Just forget to add deploy_key to this repository.

Change input of ctc error evaluator in the test

to restore successful build status. travis DOCS job on master failed due to permisstion issue: https://travis-ci.org/baidu/Paddle/jobs/159851334  @reyoung, please resolve the permission issue.

* Add documentation build to ci test
* Push master branch doc changes to gh-pages branch

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

Merge Baidu Internal Changes.

Change-Id: I8e0a8ea6fc2760652d9c76440a539c90860062d3

* modify RecurrentGradientMachine to support hasSubSeq sequence inlinks with the same number of sentence but different number of tokens for each sentence

Change-Id: Ic71f00a4bb346b4fa93e650dfb4b1a0d8d2338b0

Change-Id: Id66da7b7f5bf9ec80cc19b347e4fb822a5a6f197

* by default, synchronize default_stream after resizeAndCopyFrom
* add sync in some places after resizeAndCopyFrom using other streams