* constant folding/trt subgrash pass debug
* constant folding set persistalbe var in OP block, and remove unsed log
* set node var persistalbe

* disable scale op in amp pass

* Do not insert redundant cast op

* fix fused_fc_elementwise_layernorm kernel diff

* fix fc kerenl diff

* [Release2.4] Revert python link prs (#48573)

* Revert "Fix mac link python (#48017)"

This reverts commit 3fa7a736.

* Revert "[Cherry-pick] Fix python link error (#47811)"

This reverts commit ff642c68.

* Update config.go

* fix mixed precision inference
Co-authored-by: NChen Weihang <chenweihang@baidu.com>

* [Release2.4] Revert python link prs (#48573)

* Revert "Fix mac link python (#48017)"

This reverts commit 3fa7a736.

* Revert "[Cherry-pick] Fix python link error (#47811)"

This reverts commit ff642c68.

* Update config.go

* [Paddle Inference] Add float_to_half_pass to support  inference with mixed precision (#47993)

* [Inference] optimize some code and fix some bug (#48780)

* clean ir_pass_manager and fix map_depthwise_conv_to_conv_pass

* fix unitest timeout

* [Paddle Inference] clean unused code  (#48392)

* fix

* update

* update
Co-authored-by: NChen Weihang <chenweihang@baidu.com>

[cherry-pick] updating mul and matmul with set_mem_desc and fix squeeze_transpose for MKLDNN (#47951)

* Fix slice bugs in MKLDNN when input dims are zeros (#46671)

* fix slice bugs

* fix

* update code

* fix

* update code

* updating mul and matmul with set_mem_desc (#45624)

* - mul & matmul changes

- fix

- bs16 correction of strides

* - cosmetic fixes

* - lint

* - fix

* - fix

* - format -> mem_desc

* - fix

* - fix

* - fix

* - fix

* - fix

* fix squueze_transpose (#47911)
Co-authored-by: NJacek Czaja <jacek.czaja@intel.com>

* add fuse_multi_transformer_layer_pass

* suqeeze2 + transpose2 fuse onednn cherrypick 2.4

* format

* fix merge

* fc cherrypick

* another files added

* added transpose cherrypick

* reverter somebodys fc changes

* minor fix

* minor fix

* cherry-pick of fc+act changes

* minor fix

* fix

* add constant_folding_pass pass for mkldnn int8

* update UpdateScaleOpInOutScales

* fix memory copy in prepare_data. test=develop

* add cache_kv fp16 support. test=develop

* fit for simplify_with_basic_ops_pass. test=develop

* add fused_attention_pass. test=develop

* support fp16. test=develop

* fix format. test=develop

* Fix quantize model deploy bugs when using MKLDNN (#45920)

* fix immutable op quantize bugs

* fix

* fix build bug

* fix test

* notest,test=inference

* fix ppyoloe acc drop bugs

* fix test

* fix test

* add test

* fix

* fix

* fix test

* fix refined name bug

* fix test

* bias fix

* fix matmul weight dequant bug

* re-ci

* fix tester

* fix test

* fix tester

* update weight dequantize func

* update code

* update test for converage

* update test

* update cmake

* update cmakelist

* update code

* rerun ci

* remove useless code

* re-ci

* update code

* update code

* fix header

* update code for log

* Enhance the layernorm shift partation fuse op when shift size > 0 (roll shifting)
* fix cherry-pick test

* Add unsigned int8 propagation

* Add or modify unit tests

* Correct concat scale checking

* Apply review suggestions

* Corrections
Co-authored-by: Njoanna.wozna.intel <joanna.wozna@intel.com>

[CherryPick][Dy2St]Fix recurrent op eager deletion pass error in dy2st

* paddle-inference support custom-ops
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>

* fix tolower
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>

* [PHI] Migrate gelu kernels (#45596)

* gaussian random

* mkldnn to onednn renaming

* fix merge conflicts

* remove fluid code

* onednn renaming

* gelu fwd

* sort activations

* gelu gradient

* remove unused macros

* merge conflicts

* fix merge conflicts

* remove extra contraint from gelu op

* [PHI] relu6_grad kernel (#46501)

* Relu6

* remove fluid handler

* add individual kernel signature

* coding style

* replace bounded_relu with clip

* whitespace

* code style

* fix preln_residual_bias_fuse_pass bug in TNT_small model

* fix wrong eigen header include

* fix complie bug

* fix nan_inf_utils_detail

* fix resource_manager

* fix conv_miopen_helper

* first commit

* conver done

* correct format

* layernorm_shift_partition

* correct convert

* redefine plugin

* runable

* bug fix

* modify ShiftPartitionPattern

* correct

* add UT

* modify ut

* compile

* modify enforce

* modify UT

[Paddle Inference] fix bugs in quant_conv2d_dequant_fuse_pass when weight is shared  between ops (#45719)

* fix_old_format

* fix bug in quant_conv2d_dequant

* fix bug in quant_conv2d_dequant

* support onnx format quantized model

* update code

* add test

* add test

* fix

* fix test

* fix cmake

* update code

* change scale file path to calibration file path

* update code

* update code

* fix build bug

* fix build bugs

* fix

* fix

* fix: vit attention pass

* reflash CI

* add del dropout op pass to jit pe enigne

* add delete dropout test

* add runtime config in phi

* add runtime attr for op desc and op

* fix no proto error

* adjust opdesc set_attr impl

* try to remove conv_op extra attrs

* add init runtime attr map

* change extra header path

* fix runtime_attr

* fix trace_op

* fix bug of pass

* fix merge conflict

* fix dygraph attrs

* fix bug of pass

* fix dygraph bug

* fix unittest module

* delete extra attr default

* fix dropout kernel

* polish code

* fix extra output of instance_norm

* fix merge confilct

* fix op_desc bug

* add extra attr in yaml for conv3d_transpose

* don't remove extra input and output

* fix save_inference_model

* fix bug of batch_norm

* revert some change

* polish log

* polish code

* add code comment
Co-authored-by: NChen Weihang <chenweihang@baidu.com>

add constant folding pass， for some model，it will get less latency；

* add interpretercore

* refine backward program id

* add code

* refine program

* refine code

* create forward/backward_program by prog2graph2prog method

* test, do not care

* refine code

* refine code

* refine code

* test, do not care

* add interpretorcore

* add scope

* refine scope create method

* add jit for new_exe

* solve conflict

* delete unused code

* polish code

* polish code

* refine scope in inplace

* refine for datatransfer

* refine _rebuild_from_desc

* refine control eager deletion attr

* refine used_for_jit

* refine jit for infer

* op size0 use ori program

* polish code

* refine jit

* refine run_program_op ut

* refine inplace

* refine control

* refine graph helper

* refine control

* refine inplace

* refine buffer_share_inplace_pass

* polish code

* polish code

* refine usage for compilerProgram

* refine control

* test

* test core cache

* refine code

* refine io.py

* increase test_seq2seq timeout

* refine convert program

* refine interpretercore_cache release

* delete buildinplace

* refine partial_program && io

* refine code for io

* test

* test

* test

* Add int8 support for matmul+elementwiae_add fuse

* Corrections after review and ernie test fix

* merge conv_concat_relu to conv_act

* fix typo

* extend unit test

* reuse existing gpd

* codestyle

* enforce mkldnn conv

* convert multihead to oss

* fix:bug

* fix:delete const cast

* fix:don't support bias_qk

* add vit pass

* fix:convert bug and add preln_residual_bias

* support length=-1

* add UT for convert

* add no_bias_qk support for gpu_multihead_op

* delete infer_shape depends on bias_qk

* oss just can be used in T4 and A*

* fix:change api for ROCM CI

* remove v2_transpose_reshape

* matmul_transpose_reshape

* reshape_transpose_matmul

* Add int8 support for matmulV2

* restore ut

* adjust old ut

* restore parallel UT ruels

* remove mkldnn code from base ops

* move enforces to pass

* remove duplicated functions

* delete duplicated enforces

* feedback from review

* add comments to variables

* enable eltwise support

* dynamic attribute

* remove fusepass tests from op test

* remove fuse pass cases from op test

* revert introduction of dynamic attributes

* style
Co-authored-by: Nwozna <joanna.wozna@intel.com>