* fix a infer bug of understand_sentiment.

* this is a test pull-request, test=release/1.8

* fix doc, test=release/1.8

* fix doc, test=release/1.8

* fix doc, test=release/1.8

* Upgrade APIs for word2vec & label_semantic_roles

* Some more fixes

LGTM

LGTM

* add cn doc of trace API

* update understand_sentiment to 1.8

* add chinese guider for plsc

* removefill_constant_batch_size_like  gaussian_random_batch_size_like  uniform_random_batch_size_like_cn API doc test=develop

* add en docs for gan

* update

* update

* update index

* add disable_dygraph enable_dygraph en cn docs
test=develop

* clean DS_Store
test=develop

* update_fluiddoc_0228,test=develop

* Update release_note_cn.md
Co-authored-by: NDaniel Yang <grasswolfs@163.com>

* fix Fluid Doc deploy elastic ctr on baidu cloud, image deadlink error test=develop

* remove dead link

* Update machine translation in book for 1.7

* Update index.cn.html in machine translate

* Updata the format errors of machine translation in book for 1.7

* Small fix of print in machine translation in book.

upgrade api for rec_case

* update data api

* del left name_scope docs
test=develop

* minor fix
test=develop

* add explaination on model.eval(), test=develop

* follow comments, test=develop

* fix dead links for models

* fix_dead_links

update x2paddle link

* update DetectionMAP reference

* Update DetectionMAP_cn.rst

* update paddle version in DyGraph.md, test=develop

* update paddle version in DyGraph.md, test=develop

* Add picture for deploy_ctr_on_baidu_cloud_cn.rst

* Baidu yun K8S + Volcano CTR Training Document 1.0

* Add ctr_pserver_log.png for deploy_ctr_on_baidu_cloud_cn.rst

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Add pserver-log

* Update deploy_ctr_on_baidu_cloud_cn.rst

* chanage image of kubectl download version from 1.13.3 to  1.13.4

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Update deploy_ctr_on_baidu_cloud_cn.rst

Update on Sept 18. 
remove description of helm, tiller, Go install.
replace new yaml provided by Jinghui Zhang

* add some images

* Update deploy_ctr_on_baidu_cloud_cn.rst

add model output manipulation part

* Update deploy_ctr_on_baidu_cloud_cn.rst

* update deploy ctr on baidu cloud cn.rst

* auto convert from md

* Update deploy_ctr_on_baidu_cloud_cn.rst

* replace the overview.png

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Delete train_on_baidu_cloud_en.rst

it is outdated and cannot match with Chinese Version for months.

* Delete train_on_baidu_cloud_cn.rst

Has been replaced by ELASTIC CTR

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Update deploy_ctr_on_baidu_cloud_cn.rst

* Update deploy_ctr_on_baidu_cloud_cn.rst

test=document_fix

* add cn docs, test=develop

* refine docs, test=develop

* add program doc, test=develop

* fix links, test=develop

* fix links, test=develop

* fix links, test=develop

* fix links, test=develop

* Fluid -> Paddle, test=develop

* Fluid -> Paddle, test=develop

* minor fix, test=develop

* minor fix, test=develop

* add save load save_dygraph load_dygraph, test=develop

* add .idea in gitignore, test=develop

* minor fix, test=develop

* doc refines, test=develop

* doc refines, test=develop

* add stop_gradient notes in Dygraph, test=develop

* add stop_gradient notes in Dygraph, test=develop

* polish code in Dygraph, test=develop

* polish code in Dygraph, test=develop

* polish code in Dygraph, test=develop

* add Automatic pruning in Dygraph, test=develop

* fix Dygraph cn sample code, test=develop

* fix Dygraph doc format, test=develop

new document to upload in this PR

the previous doc talks about how to run CTR training on Baidu Cloud K8S Cluster.

the new doc are modified in following points.

1.Run CTR Training on Baidu Cloud K8S + Huawei Volcano
2.Auto Split CTR model into sparse ones and dense ones.
3.Cube auto fetch Sparse model, Serving auto fetch dense model.
4.provide paddle serving client to test the ctr prediction.

* polish en doc of data_loader

* follow comments

* use fluid.data()