* test=develop, rm netifaces

* add gloo initializer, test=develop

* fix test_dist_fleet_heter_ctr & peformance update

* fix fleet util and gloo

* fix worker endpoints

* fix

* fix UT

* fix gloo

* fix gloo

* update gloo

* update gloo

* update gloo

* update gloo

* update gloo

* fix gloo wrapper for hdfs

* add file gloo and UT

* fix UT

* fix UT

* fix UT

* hide public method of RoleMaker

* fix UT

* GPU fleetrun support gloo

* parameterserver fleetrun support gloo

* add UT

* add UT

* fix UT

* fix get server endpoint

* fix get server endpoint

* fix UT

* hide public method of rolemaker

* hide public method of rolemaker

* hide public method of rolemaker

* Update test_fleet_rolemaker_new.py

* hide public method of rolemaker

* hide public method of rolemaker

* fix worker endpoints

* fix gloo wrapper for hdfs

* GPU fleetrun support gloo

* parameterserver fleetrun support gloo

* fix get server endpoint

* test=develop, util documents

* support running python train.py for fleet-task; test=develop

* Support Heter Parameter Server

* fix api document

* solve the initial configuration about fleet and rolemaker
Co-authored-by: NseiriosPlus <tangwei12@baidu.com>

* add feature to fleet2.0 role_maker, distribute_strategy, test=develop

* move paddle.fleet to paddle.distributed.fleet

* test=develop,test=document_fix, remove the out args

* fleet_util move to paddle.fleet
Co-authored-by: NWuHaobo <wuhaobo1994@gmail.com>
Co-authored-by: Ntangwei12 <tangwei12@baidu.com>

* add paddle.fleet.DistributedStrategy for 2.0

* fix high level API(Inference) bug

* patch the unit tests

* Use for_test=True in the Fluid Trainer to clone the test program

* fix typo

* Should do the samething to the inferencer

* add Inference.infer

* optimize code

* update no_test_word2vec_new_api.py

* update trainer

* split check_and_get_place

* use inference_program to save inference model in Trainer

* update demo

* update save_inference_model

* clean code

* Load/save the params from the params_path

* Switch to use load_persistables and save_persistables

* Instaed of setup the executor to run program and scope. Pass the program to the load_persistables

- The trainer and inferencer will load params from disk if param_path
  argument is not None in their constructor.

- Remove params.py, we will expose core.Scope to the user if needed
  (e.g., for GAN). Currently we will not expose it, unless we clearly
  know doing so can support GAN.

- Add `save_params` to Trainer (a TODO item).

- rename "network" to "program"

* "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

* Fix lots of trainer_config_helpers bug, and complete unittest for `layers.py`