* Enhence generate_proposal_labels_op
* Fix bug in generate_proposals_op
* Refine rpn_target_assign_op.
* by Bu Xingyuan, Wang Guanzhong and Dang Qingqing

* trainer auto wait pserver port ready

* add file

* fix docstring

* add option to not wait

* update api spec

* clean

* fix test hang

import os module to use os.environ in setUp()

* add ignore index

* update api.spec

* enhance softmax_with_cross_entropy

* Implement norm_op by CUDA instead of Eigen.
* Remove the commented code.

* add save_inference_model for Trainer

* add comment

* update comment

* fix mac compile

* add unit test

* update API.spec

* revert cpplint-cpp-source

* Add intermediate

* fix flatten/squeeze/unsqueeze

* Considering compatibility issues, we could not fix the origin op

* follow comment

* reset the shape of XShape

* rmsprop optimizer support v1 mode

* typo

* optimize code

* refine code

* optimize unit test

* update test_rmsprop_op.py

* update formula of rmsprop

* optimize document

* update API.spec for RMSPropOptimizer

* add default value to check_output_with_place equal_nan

* reimplement auc in pyton

* reimplement auc in fluid

* add auc unittest


* replace new auc in layers


* add batch Auc in Fluid

* name formated

* Refine fusion lstm op code for better readability

* Enable peephole in fusion lstm op (seq_mode part) and add unit test

* Enable peephole in fused lstop op (batch_mode part)

Set batch_mode as default as well

* Use pre-commit to clean format

* Follow up review comments as well as adding more unit tests for seq mode

Resume prelu_op_test in python2

* Fix bug in generate_proposals_op.
* Fix data type for RoIs.
* Refine and fix rpn_target_assign_op.
* Add the missing file bbox_util.h
* Rename BoxEncoder to BoxToDelta

* fix high level API(Inference) bug

* patch the unit tests

* Improve and fix fake_quantize_op.