* update trt engine to set in/out data type

* update

* Update engine.cc

* Update engine.cc

* update

* set engine output type before freeze the network

* update

* update trt autoscan ut

* update

* update ut

* fix equal bug, update ut

* fix cast and equal ut

* update cast ut using TRT < 8.4

* set datatype from scope

* check output var is nullptr

* Update op_converter.h

* update tensorrt_engine_op_test ut

* update

* clear ProcessGroupCustom manually

* fix bug

* fix bug

* move destroy ProcessGroup to ProcessGroupIdMap

* enable destroy to all device

* remove unused comments

* change to internal api

* Update process_group.cc

* Update process_group.cc

* update get_device to custom

* add custom_device api

* rm is_compiled_with_custom_device from framework

* add todo comments

* support elementwise base func

* fix compiling error and add test

* remove additional param

* support vjp for div using comp

* remove additional change

* fix dy2st error with magic num

* fix dy magic num

* another magic

* another magic

* add more test

* fix windows problem

* another magic

* fix windows compile

* invoke ci

* add skip rename strategy

* support add vjp

* fix test_tanh

* support add with new axis cal

* fix resnet and some test

* add composite log

* support sub vjp

* [Eager] polish some apis logic

* polish api logic

* kunlun add support for c_concat and c_split

* replace mutable_data() and ShareDataWith()

* fix xpu unittest issue: zero_dim_tensor

* deal with leftout issue introduced by #49470

* [PHI] rrelu add yaml

* polish

* polish

* [Eager] polish some api logic

* fix split

* revover

* lerp support 0 Tensor

* fix lerp grad

* fix lerp zero test

* fix 0D + ND/ND + 0D

* fix check

* update code

* fix lerp infer shape

* static backward test

* updata static graph test

* Fix reduce func bug in process_group_bkcl

Also catch up with a recent process_group PR that failed to add XPU branch.
Note that reduce is still accomplished by allreduce for xpu. Fix this should
xccl lib be updated.

* fix compile issue for non-XPU

* compile fix

* fix compile

* compile fix

* add more preln

* [Zero-Dim] support input 0D Tensor for maximum,minimum,allclose,sigmoid_focal_loss

* [Zero-Dim] add backward test for sigmoid_focal_loss with 0-D input Tensor

* [Zero-Dim] support input 0D Tensor for fmax,fmin,complex

* recovery annotation

* bugfix

* remove Travis CI build status badge from README.md

* empty commit, test=document_fix

* Add tools for quantization-aware training
1. Expose an API named paddle.quantization.QAT
2. Define a wrapper class to insert quanters into model for QAT
3. Add some functions in QuantConfig for QAT
4. Add unittest for QAT

* Add QuantedConv2D and QuantedLinear for QAT

* Add paddle.nn.quant.qat to setup.py

* [D2SCinn]Fix self.infer_program always build cinn pass without cache

* fix infer op size

* add FusedLinear pass

* add fused_op_list and renname PASSES to OP_FUSION

* add fused_passes_list to constants.py

* add test_passes.py

* fix test_fused_passes.py

* fix add if float(paddle.version.cuda()) >= 11.6:

* renamed test_fused_passes.py

* fix CMakeList.txt

* add enable_to_static and drop some methods of ProgramTranslator

* fix code style

* fix cant import enable_to_static and update unitest

* change unitest and rollback code of PT

* fix can't import as of utils

* roll back PT

* fix roll back

* add some unitest

* add unitest and fix codestyle bug in api.py

* finish all unitest

* remove ProgramTranslator

* fix code style

* restore test_program_translator

* api.py remove get_func

* TestDygraphToStaticCode

* fix check_type and import err

* roll back PT without getcode

* roll back pt with get_code

* convert_to_static

* fix import __all__

* fix nll_loss

* fix nll_loss

* update

* update

* update

* fix

* rm retain_grad_flag for tests

* modify transpose op

* retain grads for xpu tests

* lint

* modify xpu test

* refactor: gloo comm context migration

* fix: headers & avoid mutable_data usage

* fix: cmake gloo dep

* style: rename funcs

* refactor: move to new files

* fix: gloo deps

* refactor: simplify create device

* [Zero-Dim] support input 0D Tensor for maximum,minimum,allclose,sigmoid_focal_loss

* [Zero-Dim] add backward test for sigmoid_focal_loss with 0-D input Tensor