* add attribute for batch_norm

* fix 2.0 api, test=develop

* fix api, test=develop

* fix examples, test=document_fix

* fix, test=document_fix

* fix syncbn

* add unittest

* upgrade comment string to raw string

* fix string in

* fix string with ' '

* revert update on comments

* upgrade only necessary

* fix sample code checker

* fix comments with '''

* Release 2.0rc cherry pick api rename #28108 (#28184)

* rename count_include_pad-->exclusive  return_indices-->return_mask

* remove track_running_stats

* fix typo.

* rename xxxd-->xxxxD

* solve conflicts

* 2.0rc api add all any (#28199)

* reduce trt warning message (#28011)

add paddle.enable_static() on sample code

alias recude_all-->all, reduce_any-->any

add import reduce_all and reduce_any in python/paddle/tensor/math.py

import all and any in python/paddle/tensor/__init__.py

remove all and any OP in python/paddle/tensor/logic.py, add all and any OP in python/paddle/tensor/math.py

fix import error

remove TestAllAPI temporary

* fix doc of recdue_all and reduce_any, test=document_fix

* fix typo

* fix unittest for all and any API
Co-authored-by: NPei Yang <peiyang@baidu.com>

* rename conv_transposeXd-->convXd_transpose (#28198)

* fix sample code of reduce_all and reduce_any
Co-authored-by: NPei Yang <peiyang@baidu.com>

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug

1. support channel last in BatchNorm*d (#27875)
2. fix a bug in batch_norm_op cuda kernel by extracting ResizeToChannelFist(Last), TransToChannelFirst(Last) to operators/layer_utils.h

* fix norm api doc, test=develop

* fix error message, test=develop

* fix api norm, test=develop

* add adagrad, test=develop

* fix bug, test=develop

* fix bug, test=develop

* add spetral_norm, test=develop

* fix adagrad, test=develop

* merge , test=develop

* add local_response_norm in nn.functional and nn.layer, test=develop

* update layers to functional api, test=develop

* fix ci coverage, test=develop

* fix unittests bug, test=develop

* fix 2.0api, test=develop

* fix, test=develop

* fix norm bug, test=develop

* fix norm bug, test=develop

* fix norm bug, test=develop

* fix norm bug, test=develop

* fix norm bug, test=develop

* add cnvert,test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* add norm 2.0 api, test=develop

* fix syncbn, test=develop

* fix test,test=develop

* fix unittest,test=develop

* add SyncBatchNorm,test=develop

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

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

* add instance_norm op for dygraph, test=develop

* add error message, 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"