* add adaptive_avg_pool2d

* add adaptive_avg_pool3d

* add pad func

* add pad

* test=develop, add pad op and apis

* restore pad2d

* test=develop, fix paddl declare

* fix pad interface

* test=develop, fix pad

* test=develop, add all pad api and cos_sim

* test=develop, remove padding default value

* test=develop, rename var to tensor

* test=develop, add more tests

* test=develop, rename tovar to totensor

* test=develop, fix init

* test=develop, add more test

* test=develop, add more tests

* add SyncBatchNorm,test=develop

* add Class KLDivLoss and function kl_div

add the api and doc for the margin_ranking_loss and MarginRankingLoss

add pairewise distance for the paddlepaddle api 2.0

* add Pad2D and Leaky_ReLU, test=develop

* update,test=develop

* change name,test=develop

* add unittest and redine docs,test=develop

* test=develop add linear interpolate operator

* define fluid alias in paddle.tensor and paddle.nn dir test=develop

* from layer import loss in paddle.nn dir test=develop

* add approximation for gelu, test=develop

* add functional conv

* add test and doc for function convs, test=develop

* update ConvTransposeOp's InferShape and error message, test=develop

* add hsigmoid, row_conv in paddle.nn(functional and layer), test=develop

* fix hyperlinks in docstring

* add instance_norm op for dygraph, test=develop

* add error message, test=develop

* add Conv/ConvTranspose layers in paddle.nn.layer, test=develop

* add example code in docstring, test=develop

* update unittests to work with test_runner, test=develop

* add L1Loss

* support L1Loss, test=develop

* add test, test=develop

* fix batch, test=develop

* follow comments, test=develop

* 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`