* new general transformer inference support

* support yolov5s static/int8

* fix eltwise_sub and div weight compute

* fix delete_fill_constant_pass

* [IPU] fix ipu and add python infer api, test=develop

* [IPU] add paddlepaddle-ipu package name, test=develop

* [Paddle-Inference] support transformer generation: some passes

* Add int8 scales gathering pass for convolution

* Fix typo

* Add unittest

* Add corrected unit test

* Change test name

* Remove enabling mkldnn in test

* Speed up test

* Change max examples

* Add functional test

* Change test name

* Add new test case

* Rename pass

* Readd conv_affine_channel fuse pass as mkldnn pass

* Fix formatting

* Add new test to parallel_UT_rule.py

* Fix Coverage and Windows CI issues

* Revert "Fix Coverage and Windows CI issues"

This reverts commit f33459846385c9fd51c07f9f44e7ff283a652637.

* Fix CI errors

* Remove unnecessary conv_eltwise_add_affine_channel fuse pass

* Remove test from parallel_UT_rule.py

* rm transfer_cast_op_pass

* rm header

* added test for shuffle_channel_mkldnn_detect_pass

* added UT using new framework

* CI fix

* Change tensor name to match activation

* declare fc_eltwise_add pass

* merge conv_eltwise refactor PR

* first compilable draft

* unittest feedback tools

* Fuse pass tester

* Move IsReachable() to shared file

* 100% coverage of fuse_pass_tester.cc

* register pass

* Add bias node

* Improve unit tests / remove bias node from pattern

* improve fc_eltwiseadd_unittest

* cancel eltwise_add fuse if act is already fused

* Add elementwise_input scale

* Residual MVP

* Add new FC attrs

* Add more test cases

* Add missing op attrs

* Adapt code to new Elementwise pattern

* reuse existing fcpattern

* improve code style

* remove unused arguments

* fix typo

* remove whitespace

* remove int8 related code

* Remove attributes from base ops

* style

* style check

* Remove input from base op

* Set attribute during fuse

* ut timeout

* download and test model

* DRY

* apply feedback from review

* Style check

* fix typo

* cosmetic changes

* explicitly set residual as output

* VIT-OCR accuracy check

* trigger CI

* remove whitespaces

* fix missing data file

* add mkldnn int8 pass [step3]

* Add test for compute_propagate_scales_mkldnn_pass

* update pass

* update api comment and python api
Co-authored-by: Nwozna <joanna.wozna@intel.com>

* added shuffle_channel bf16/fp32 fwd kernel

* added missing files

* CI fix

* changed from pten to phi

* tmp save

* added reviewers suggestions

* fix for test

* add mkldnn int8 pass

* add mkldnn int8 pass

* update pass

* remove paddle_ipu shared library

* fix unique_name

* paddle inference support new quant_model

* Add elementwise add and activation fuse pass

* Fix copy ellision

* More flexible pattern detector

* More flexible fusion pass

* Update lists for pass

* Add support for Pow operator

* Add support for more activation types

* Style

* Rename fusion pass

* First version of tests

* Dirty version of pass

* Polished version

* Update pbtxt

* Style

* Update names

* Style

* Use PADDLE_ENFORCE_EQ

* Save error message to variable

* WO for error checks

* CR

* Static style check

* Add missing 'activation_scale' attribute

* Add relu6 and sigmoid activations

* Style

* Fix fuse list formating

* Sync filenames for fuse pass files

* Fix cmake after move

* Fix registration

* Fix pass name in tests

* Add missing activations to checker

* WIPS

* Working mul op

* Working sub

* Working Add

* Remove pten includes

* Remove some forward declarations

* Remove Includes

* Fixes

* Remove default kernels

* Add check if post_ops attributes are avaliable

* Style

* Code adjustment

* Register default kernels

* We have year 2022 not 2021...
Co-authored-by: Njakpiase <jakpia21@gmail.com>
Co-authored-by: NSylwester Fraczek <sylwester.fraczek@intel.com>

* Fast review fixes
Co-authored-by: Njakpiase <jakpia21@gmail.com>
Co-authored-by: NSylwester Fraczek <sylwester.fraczek@intel.com>

* Review Fix

* Rename one_dnn -> onednn

* Style after review

* Fast and dirty fix for quantization

* Update tests

* Style

* Fix mkldnn_quantizer config

* Add Joanna's suggestion.

* Check if operator is explicitly disables on OneDNN

* Try to use unregistered attributes

* Style

* Test new framework

* FXI

* FXII

* Update test

* Style
Co-authored-by: Njakpiase <jakpia21@gmail.com>
Co-authored-by: NSylwester Fraczek <sylwester.fraczek@intel.com>

* Added cuBlasLtHandle_t to device context.

* Added fused_gemm_epilogue op.

1. Added fused_gemm_epilogue op to leverage cuBlastLt Epilogue.
2. Support fusion Act(X*Y + bias), X'dims >=2 and Y'dims shoule be 2.
2. Act currently only be supported ReLU. (Will add GeLU in the future).

* Added UT to fused_gemm_epilogue op.

* Added LinearAct Pattern

1. Added LinearAct into graph_pattern_detector.* to define (2.)'s
pattern.
2. LinearAct is used to detect act(element_add(matmul_v2(x, w), bias)).
3. act currently only support ReLU (Will support GeLU in the future).

* Added FuseGemmEpiloguePass

1, Added FuseGemmEpiloguePass to handle nn.Linear + Act{ReLU}
fusion (GeLU will be supported in the future).
2. Only support matmul_v2 from nn.Linear.

* Added pybind to BuildStrageter.fuse_gemm_epilogue_.

* Added UT for fuse_gemm_epilogue_pass.

* GeLU support and EpilogueSingleton

1. Added GeLU support to fused_gemm_epilogue op.
2. Added EpilogueSingleton to cache auxiliary pointer.
3. Added related UTs.

* Rename cublaslt_epilogue_opto gemm_epilogue_op.*.

* Added both train and infer pattern to LinearAct.

1. Added support of fwd graph with grap_ops linking to LinearAct.
2. Added related changes to fuse_gemm_epilogue_pass for above
modification.

* Changed CUDA requirement from 11.4 to 11.6 for fuse_gemm_epilogue_pass.

* Added identity activation support to gemm_epilogue_op.

* Added Linear Fusion (matmul_v2 + ele_add)

1. Added matmul_v2 + ele_add pattern to LinearActPattern.
2. Added matmul_v2 + ele_add support to fuse_gemm_epilogue_pass.

* Rename gemm_epilogue_op.* to fused_gemm_epilogue_op.*

* Add fused_gemm_epilogue_grad op.

1. Added fused_gemm_epilogue_grad to support backward epilogue fusion.

* Add UTs to fused_gemm_epilogue_grad_op.

* Change attribute name in fused_gemm_epilogue_grad_op for clearing.

* Allow DX and DBias be dispensable to fused_gemm_epilogue_grad op.

* Added ElementwiseAdd+Matmul+Act graph pattern detection.

* Fuse backward of Linear( Act(x))

1. Added backward fusion pass to Linear( Act(x)).
2. Added backward fusion pass to Linear(x).

* Added UTs to backward fusion of Linear(Act(x)).

* Complete document of arguments to fused_gemm_epilogue_op.

* Made arguments of some functions pass by reference.

* Modify code with review comments.

1. Made arguments of some function pass by reference.
2. Removed redundant code.
3. Followed Google code style to change code.

* Made 'const' code style be consistent

* Fixed random seed of python UTs.

* Set Compiling constrains to cuBlasLt

1. Require CUDA 11.6+
2. Remove fuse_gemm_epilogue related tests when CUDA < 11.6.

* Code Reivew from Paddle

1. Changed arguments name is_first_gemm to without_x_gradient for
clearing.
2. Applied PADDLE_THROW in fused_gemm_epilogue_op.

* Remove EpilogueSingleton

1. Applied ReserveSpace to replace Epilogue for passing auxiliary
pointers between FWD and BWD.

* Fix a logical error and enhance UTs.

1. Added act op count checking in UTs.
2. Fix issue to fuse backward or ReLU(Linear(X)).
3. TODO: solve GELU fusion issues.

* Fix Linear and GeLU fusion issues.

1. Modified graph_detech_pattern to fit with both linear wiht gelu or
relu.
2. Modified data range in Uts to allow negative values.

* Removed fused_gemm_epilogue_op.h.

* Rename namespace pten to phi.

* Rename name of arguments in fused_gemm_epilogue_op

1. bias -> Bias.
2. out -> Out.
3. reserve_space -> ReserveSpace.

* Change EpiloguePassActivationCache as local variable.

1. Removed singleton in EpiloguePassActivationCache.
2. Made EpiloguePassActivationCache as an argument to each pass
functions.

* remove

* pass

* more pass

[Paddle-Inference] support preln_ernie: add preln_embedding_eltwise_layernorm_fuse_pass, preln_skip_layernorm_fuse_pass (#39508)

* support preln_ernie

* support preln_ernie

* rebuild matmul pass: trt and gpu_cpu

* rebuild matmul pass: trt and gpu_cpu

* rebuild matmul pass: trt and gpu_cpu

* rebuild matmul pass: trt and gpu_cpu

* sync misc changes

* apply comments 01

* fix compile error

* remove is_ipu_place check

* add authors
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NAllen Guo <alleng@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NHaicheng Jiang <haichengj@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

* sync changes

* restore cmake

* update ir cmake and setup.py

* update inference_lib cmake

* split PR
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NHaicheng Jiang <haichengj@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

* add matmul_scale matmul_v2_scale fuse pass

* add scaletensor judge

* modify var name

* add timeout notest;test=coverag

* fix error commit

* fix use_mkldnn attr

* fix use_mkldnn attr

* add test for conv_elementwise_add2_act_fuse_pass and conv_elementwise_add_act_fuse_pass

* Add conv_eltwiseadd_bn_fuse_pass test and fix test_conv_elementwise_addX_act_fuse_pass

* add tests for conv_act_mkldnn_fuse_pass

* add test for conv_bias_mkldnn_fuse_pass

* update code

* add conv_act_mkldnn_fuse_pass for relu, relu6, swish, leaky_relu

* update test

* update

* update bug

* update

* update pattern_detector

* fix test_conv_eltwiseadd_bn_fuse_pass

* add diff display notest;test=windows_ci_inference

* fix

* remove test_conv_act_mkldnn_fuse_pass.py

* ifix

* add layer_norm_fuse_pass test case

* restore cmakelist code

* Merge branch 'develop' into layer_norm_fuse_pass

* Merge branch 'develop' into layer_norm_fuse_pass

* add bad case test

* reshape+transpose+matmul_v2

* in_name->input_name

* fix pr-ci-static-check

* add fc_elementwise_layernorm_fuse_pass

* fix name conflictn

* rebuild CI

* fix Ran Programs=0 bug

* add test_unsqueeze2_eltwise_fuse_pass

* fix name conflictn

* rebuild CI

Add test property RUN_TYPE=CINN to CINN unit tests. It will restrict Paddle-CINN CI to run these unit tests only.

* added softplus + activation fuse plass

* minor change

* implemented reviewer suggestion

* minor fix

* minor fix

* added scale_out parameter

* minor fix

* fix for iScan CI

* conditionally disabled logs

* refactored pass builder

* added base changes for matmul_v2+trans+resh fuse pass

* added full matmul_v2+transpose+reshape pass

* removed a file added by mistake

* added reviewers suggestions

* Changed ops type in checking capatibility version

* Deteled one statement

Add CINN compile option in CMake.

Now you can use CINN in Paddle by `-DWITH_CINN=ON` when `cmake`

To test it, you can run `make cinn_lib_test -j` and `ctest -R cinn_lib_test`. 

Note:
1. You should set
```
export runtime_include_dir=${CINN_SOURCE_DIR}/cinn/runtime/cuda 
```
When run test, the `${CINN_SOURCE_DIR}` should be set based on your CINN directory.

2. CINN is under developing now, you may have to change `CINN_GIT_TAG` to the git commit you need.

* Add CinnSubgraphSearchPass

* solve CI problem of subgraph order not same

* fix some bug by review advices

* ensure the independently of subgraph, that mean the subgraph should not have link to out-graph

* rename cinn_subgraph_search_pass to build_cinn_pass and delete paddle_to_cinn_pass

* add flag to control wheter append build cinn pass

* remove AppendPass at ParallelExecutorPassBuilder

* rename paddle_to_cinn_pass to build_cinn_pass in build_strategy and close test_run_from_cinn

* add_int_pass

* add_int8_flag_pass

* add_int8_flag_pass

* fix CMakeLists.txt

* fix test_trt_fc_fuse_quant_dequant_pass.py

* fix python/paddle/fluid/tests/unittests/ir/inference/test_trt_fc_fuse_quant_dequant_pass.py

* fix test_trt_fc_fuse_quant_dequant_pass.py

Add use_cinn flag and use it to control whether we run PaddlePaddle using CINN.

Also add:

Replace PaddlePaddle graph with a CINN graph in a pass
PE Method to feed data and run the graph by CINN

Add basic Cost Model, it uses executor to run program and profile it to get op time.

This is an early basic version, we will add more functions in the future.