* support negative index in unique_consecutive

* add unittest

* add unittest

* replace matmul with matmul_v2 in fuse passes

* Remove fusion logic from matmul

* removing fusion methods

* add proper name

* adjust namespaces

* clean attrs in python tests

* delete checkpoint and restore matmul version

* remove unused code

* matmul and reshape/transpose fuses migrated

* split MatmulOneDNN headers

* fuse activation and eltwise_add

* add fuse_activation

* matmul_transpose_reshape/reshape_transpose_matmul

* matmul + elementwise_add (fused)

* activation temporary modifciation

* merge newest develop

* remove depedency from other PR

* revert pbtxt

* remove placeholders from matmul_v2

* add description in OPMaker

* remove matmul_v2_op.h and all depedencies

* remove dims changing in base op

* add possibility to fuse already fused_matmul

* restart broken CI

* Empty-Commit

* revert matmul_utils.h

* codestyle

* adjust imports

* add pbtxt file

* 100% matmul unit tests coverage

* trigger CI with minimal changes to develop

* adjust changes to develop

* add fused_matmul op

* inherit base ops

* add "v2"

* move OPMaker

* Gradually add fused_matmul files

* second batch of fused_matmul changes

* split infershapes of matmul_v2 and fused_matmul

* inherit fused_matmul from matmul_v2

* Update paddle/phi/backends/onednn/onednn_reuse.h
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* Update paddle/phi/kernels/fusion/onednn/fused_matmul_kernel.cc
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

---------
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* conv_bias_mkldnn_fuse_pass_tester rewritten

* conv_concat_relu_mkldnn_fuse_pass_tester rewritten

* conv_elementwise_add_fuse_pass_tester rewritten

* mkldnn changed to onednn

* tests added to cmakeLists, style fix

* got rid of unnecessary UT, some style changes

* changes in naming convention

* max_examples reduced

* time out added

* add input check for accuracyOp

* add input check for gpu/accuracyOp

* add unittest

* use rank instead of dimensions in message

* update unittest

* update unittest

* generate some static graph ops

* fix the bug of pow

* add REGISTER_ACTIVATION_OP in operators.cmake

* modify the file operators.cmake

* [Divide by 0 Error] add svd check

* [Divide by 0 Error] svd check migrate to c++, move svd test_0_size

* [Divide by 0 Error] add normalize check

* [Divide by 0 Error] normalize check migrate to c++

* fix cross_entropy

* update

Add test_resnet for prim and CINN

* Reduce time cost of BuildOpHappensBefore

* Update code

* Update code

* Improve data struct

* [dy2static] support fallback for whole graph. (stage 1)

* bug fix

* bug fix and add a new unittest

* fix code by code review

* fix coverage

* optimize log

* fix type error

* fix type error2

* refactor dir for prim

* support blacklist for bwd comp

* fix type error

* remove additional file

* fix git ignore

* add more test

* merge develop

【PRIM】Support use operator's output metadata info  in constructing static backward composite (#50043)

* [prim] support custom target_gradients

* support infershape after append one gradop

* [prim] add simple net test

* fix test_loop segment fault bug

* [prim] fix infer shape segment fault bug when output of grad_op_desc is empty

* add stride check for PoolOutputSize

* add unittest

* add dimension check for nce

* add unittest

* fix incorrect type in test_nce

* fix bugs in cluster to device meshes

* add tests

* 1

* add input dimension check for max_unpool2d/max_unpool3d

* add unittest

* paddle.nn.functional.softmax
* paddle.nn.functional.log_softmax
* paddle.nn.functional.gumbel_softmax
* paddle.nn.functional.prelu

* fix bugs

* fix ci bugs

* jit layer support multi thread

remove fluid.initializer.UniformInitializer, ConstantInitializer, NormalInitializer, TruncatedNormalInitializer, XavierInitializer, BilinearInitializer, MSRAInitializer, NumpyArrayInitializer and calculate_gain.. (#49498)

* move UniformInitializer and ConstantInitializer

* more modify

* circular import resolved

* another circular import resolved?

* more circular import 2

* circular import 3

* change import paddle in metric.py

* BuildStrategy import from fluid

* modify the framework import path in common.py

* change rnn.py import, from static to original framework

* change import static in the nn folder

* default_main_program should import from common_ops_import

* add import paddle in param_attr.py

* use core not paddle module for using VarDesc

* another old uniform

* mistake that use Uniform instead of UniformInitializer

* modify UniformInitializer doc

* move fluid.NormalInitializer to nn.initializer.NormalInitializer

* remove import of Normal in fluid.layers.nn.py

* remove more import of old Normal

* remove more import of old Normal

* sample code modify and tests modify import

* is_listen_failed passing arg should be log file

* problem solved

* a mistake solved

* comments resoleved and remove paddle.fluid.initializer.TruncatedNormalInitializer

* remove paddle.fluid.initializer.XavierInitializer and paddle.fluid.initializer.MSRAInitializer

* remove paddle.fluid.initializer.BilinearInitializer NumpyArrayInitializer and set_global_initializer

* change fluid to static

* change static to fluid to avoid circular import in distributed_strategy.py

* fix example code and test_initializer

* ValueType

* sample code fix

* change set_global_initializer back to fluid

* put paddle.static.BuildStrategy.ReduceStrategy into the fuction to avoid circular import

* remove calculate_gain, delete BilinearInitializer and revert set_global_initializer

* change the time of using UniformInitializer, ConstantInitializer, NormalInitializer, TruncatedNormalInitializer, XavierInitializer, MSRAInitializer, NumpyArrayInitializer as few as possible

* fix argument incampatible

* fix more arg incompatible

* fix test_prelu_op_xpu.py Constant

* fix inaccurate doc

* more doc fix: default value