* [Opt Performance] Optimize custom operator performance, reconstruct python API auto-gen, add cache and use const inference

* opt AutoGradMeta implementation

* remove profiler codes

* fix unit test

* change year, 2021->2023

* fix int64_t parse bug

* add autogen code bilinear_tensor_product

* [phi] rm cc file

* autogen softmax_with_cross_entropy

* fix error in softmax_with_cross_entropy version

* add strategy force_sequential_run

* remove flag

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* [enforce.h Decouple gflags.h] Move gflags.h from enforce.h to enforce.cc

* Add gflags.h for other files

* Add gflags.h for other files

* Add gflags.h for blas_impl.hip.h

* Add gflags.h for miopen_helper.h

* adjust defalut tolerance of output and grad

* fix a bug in the grad of OpTest

* fix the type of setting defalut value in optest, both forward and
backward

* add defalut

* fix test_sum_op

* adjust tolerance

* fix the tolerance of eager

* add bf16 and fp16 to the activation tests

* remove some fixs

* fix activation

* fix fp16

* fix gelu

* fix the activation tests

* add bfloat16 specialization to singrad and cosgrad

* fix bugs

* fix bugs

* add unittest

* add skip

* add fp/bf to rrelu/rrelu_grad

* git add rrelu

* fix bugs

* add fp16 and bf16 support for instance_norm

* fix /= operator which not support bf16

* fix instance_norm_grad kernel and unittests.

* fix fp32 unittests.

* fix instance_norm_kernel and unittests.

* fix instance_norm_grad_kernel and unittest threshold.

* add fp16/bf16 for instance_norm_grad_grad op.

* add bf16 dtype check.

* fix conflicts.

* fix cpu support for fp32 op and fix type in instance_norm_grad_kernel.

* fix type in instance_norm_kernel.

* fix bf16 outputs in unittests and refine codes.

* fix dx computation.

* delete unuseful params and head including.

* add fp16/bf16 for static graph.

* fix device condiction for instance_norm op.

* fix instance_norm_grad_grad and bf16 op tests.

* fix op_test to support grad of bf16 can be compared with fp32.

* remove updates.

* add self-defined grad.

* update

* fix bug

* fix ci-windows-openblas

* fix test_partial_sum_op

* fix codestyle

* fix divide zero bug for softmax_with_cross_entropy

* change the single test way

* can run but slow. the most important is that I do not know why it slow

* remove some useless commet

* change the copyright to correct

* remove some useless change

* if repeat_times == 1, we will not use BroadcastKernel

* Optimize the performance of logsumexp

* Support zero-dim tensor

* add autogen code support for affine_grid op

* update op_compat.yaml for affine_grid

* update op_compat.yaml for affine_grid

* fix AffineGridGradInferMeta

* fix CI error

* update AffineGridInferMeta

* delete [-Wno-error=terminate], test=develop

* remove GPUps[-Wterminate],test=develop

* remove some -Wno-, test=develop

* modify ~MatmulDescriptor

* mess

* optimize setup.py

* add ninja

* mv WITH_ASCEND_CL

* mv WITH_ASCEND

* rollback

* remove WITH_ASCEND

* remove WITH_ASCEND

* [bug fix] fix pow composite

* [bug fix] for ci

* [PHI CAPI] support complex dtype kernel

* update

* add seed control

* fix bug

* add autogen code support for matrix_nms.

* update

* add strategy force_sequential_run

* fix

* fix

* fix

* fix

* fix