* support yolov5s static/int8

* fix eltwise_sub and div weight compute

* fix delete_fill_constant_pass

* Refactor Quantization

* Refactor Dequantization

* Classy solution

* Style I

* Style II

* Style III

* Use VLOG(4) for debug info

* Style IV

* DRY

* change nodes names

* add const prefix

* change asX to as_x in all files

* paddle inference support new quant_model

* Quantize elementwise mul op

* Parametrize elementwise functions

* Fix code formatting

* 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.

* Fix for split bf16 inference

* added test for pass

* changes after review

* Fix quantization next op findings

* Corrections according to the review

* Quantize nearest_interp and nearest_interp_v2

* Check if avx_core supported

* Add depthwise_conv2d to supported quantization list

* update seqconv_eltadd_relu_fuse_pass ut

* update ut

* update ut

* update ut

* 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

* remove bf16

* remove comments

* remove wrong return

* fix UT

* reshape+transpose+matmul_v2

* in_name->input_name

* fix pr-ci-static-check

* quantize slice op

* correct test

* fix code formatting

* 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

[Paddle-Inference]Add MatmulV2ToMatmul convert Pass, fix (matmul_v2, matmul, mul) convert pass, fix (matmul, mul) op_teller (#36652)

* new_Matmul2ToMatmulToMul

* new_Matmul2ToMatmulToMul

* fix paddle_pass_builder

* fix paddle_pass_builder

* fix paddle_pass_builder

* tem

* tem

* Add MatmulV2ToMatmul convert Pass; MatmulV2ToMul convert Pass

* Add MatmulV2ToMatmul convert Pass; MatmulV2ToMul convert Pass

* add matmul_broadcast_unitest

* fix op_teller

* 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

* support bert when exists matmul_v2

* update

* 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 fusion_lstm INT8 PTQ

* Correct mkldnn_cache_capacity and enable fc_lstm_fuse_pass only for this test

* Change mkldnn_cache_capacity

* Add calculation for gru op

* Correct the types

* Remove mkldnn only

* Correct mkldnn ifdef

* Remove mkldnn ifdef

* Separate mkldnn quantizer test

* Correct Windows test

* Check different cmake fix

* Revert cmake change

* Cmake change 2

* Cmake change 3

* Remove force_fp32_output from elementwise_add quantization

* Fix cpu_quantize_placement test

* Review related changes

* test version of matmul_v2

* added matmul_v2 grad kernel

* minor changes

* minor changes

* minor change for CI approval

* CI fix

* CI fix

* added squeeze and squeeze2 kernels

* CI fix

* CI fix

* CI fix

* disabled tests when compiled with cuda

* added setting format_tag by strides

* added sigmoid BF16 FWD/BWD and gelu BF16 BWD

* changes after review

* Revert "added sigmoid BF16 FWD/BWD and gelu BF16 BWD"

This reverts commit 6e3f76720b545abfcff9f6052b46b73a1e745cae.

* Revert "Merge branch 'matmul_v2_grad' into squeeze2_op"

This reverts commit 06fcf67843a4a7884eccdf67a02a03575e1d4cb8, reversing
changes made to 6e3f76720b545abfcff9f6052b46b73a1e745cae.

* minor change

* added reshape1/2 kernels

* moved some functions into private block

* CI fix

* CI fix

* CI fix

* added prelu bf16/fp32 fwd/bwd kernel

* added matmul_v2 bf16/fp32 FWD kernel

added matmul_v2 bf16/fp32 FWD kernel

* added formatting

* removed some tests due to timeout in CI

* refactored tests

* merged tests classes into one file

* minor change

* removed test guard for CUDA

* remove skipIf

* changes after review

* formated one file

* minor change

* added skipping UT in CUDA place

* - fix to #33282

* - Increased threshold for elementwise_mul_bf16 grad

* -disabled faulty UT

* - fix to approval

* base changes for split op

* 90% of split functionality added

* full fp32 functionality

* added bf16 test

* added submemory caching

* added bf test to static mode whitelist

* minor change

* enabled split op for inference

* minor fix

* minor fix

* Small changes related to BF16 fusion_gru and fusion_lstm

* Correct to pass arg by value

* Add conditions to rnn op

* Correct the spelling mistake

* Improving the test with checking activation

* Trigger CI

* Add dlnne engine runtime

* Fix log

* Remove <const_cast> and remove unrelated modify with dlnne, +clang-format

* Fix CMakeList format error

* Add copyright message

* Fix dlnne CMakeList.txt

* Add some paddlepaddle_pass to support more networks

* Fix some format bug

* Add delete dropout_op pass

* Fix some format bug

* Fix format bug

* support multihead_matmul_fuse_pass_v3

* fix compile problems

* embedding_eltwise_ln pass support lookup_table_v2

* suppoort matmul and matmul_v2 in qkv matmul

* Unification of bfloat16 enablement process and refactor

* Remove unnecessary function

* Standardize the output name search

* Add conv transpose BF16

* Share function GetWeightsTz

* Adjust to review and fix op compatibility

* Add bias to unique handler name

* Remove errors related to paddle enforce

* Add conv2d_transpose to bf16 list and kernel refator