* improve dropout (#29465)

* improve drop out

* add VectorizedRandomGeneratorWithGenerator

* fix bug

* modify according to comments

* improve dropout grad (#29605)

* improve grad perf

* fix the bug of dropout_grad (#29813)

* Softmax vectorization (#29404)

* vec softmax fw

* vec softmax bw

* add a message argument for compiler compatibility

* optimize softmax forward (#30217)

* optimize softmax forward
Co-authored-by: Nzlsh80826 <zlsh80826@gmail.com>

* Optimization grad merge performance (#29784)

* [fleet] combine amp and gradient merge, test=develop (#30086)

* fix assign_op_xpu concat_op_xpu warining (#30120)
Co-authored-by: Nliuyuhui <liuyuhui@baidu.com>

* add aarch64 and sunway kunlun lib

* minor

* optimize elementwise_add for kunlun

* update kunlun dependence

* minor

* minor

[cherry-pick 2.0] Fix bug: In dynamic mode, if start or end is negetive, __getitem__  return wrong result(#30003) (#30146)

1. when slice_item is a slice:
 1) the start of __getitem__ should be std::max(start, 0) if slice
 2) the start of __getitem__ should be std::min(end, dim)
2. when slice_item is an integer, it should be in [-dim_len, dim_len)
3. Fix error message to use accurate data

1. Type of index: int, slice(step must be 1).

2. Type of value:
 (1) int32, int64, float32, bool;
 (2) numpy.array(int32, int64, float32, bool);<Note: float64 is not supported>
 (3) paddle.Tensor(int32, int64, float32, float64, bool);

* simplify prepared op impl to improve performance

* fix kunlun compile error

* continue fix kunlun compile error

* only transform diff place when dtype diff

* fix failed unittests

* remove useless file

* polish impl by review comment

* Add Lookahead and ModelAverage Optimizer (#30004)

* test=develop, add model_average and lookahead

* Improve Index select cuda kernel (#30139)

* test=develop, add index_select_cuda kernel

* Improve performance of elementwise_add grad op (#29187)

* pass stop_gradient for cast op

* improve performance of elementwise_add grad

* use tensor copy async

* dygraph branch

* fix dygraph branch

* add ut

* make gelu fp16 computing more robust (#29484)

* Add fast path for dropout when p == 0  (#29553)

* add fast path for p == 0 in dropout

* add ut

* Layer norm fp16 (#29169)

* add fp16 for layer_norm op

* revert layernorm api

* fix forward

* fix forward

* fix backward for layernorm with fp16

* fix unit test for layernorm with fp16

* fix with_mkldnn compile error for layernorm with fp16

* 1. revert to PADDLE_ENFORCE_NOT_NULL, 2. change static_cast<float> to static_cast<U>

* fix with_mkldnn compile error for layernorm with fp16

* fix with_mkldnn compile error for layernorm with fp16
Co-authored-by: Nzhiqiu <chenqiuliang@baidu.com>

* fix layer_norm accuracy (#29434)

* Layernorm opt (#29522)

* layernorm fw opt

* layernorm bw opt

* fix typo, test=develop

* remove const dim3 for windows CI compatibility

* merge develop
Co-authored-by: Nzlsh80826 <zlsh80826@gmail.com>

* Fix compile problem when cuda_arch < 6000 (#29576)

* fix compile problem when cuda_arch < 6000

* refine code

* refine code
Co-authored-by: Nzhiqiu <chenqiuliang@baidu.com>
Co-authored-by: Nzlsh80826 <zlsh80826@gmail.com>

* support dygraph in xpu place; test=develop

* fix cpu/gpu compile error; test=develop

* fix compile error; test=develop

* fix xpu compile error; testd=develop

[Cherry-Pick 2.0][Dynamic Inplace] Support ShareInplaceVersionCounterWith for C++ Tensor (#29842) (#30105)

Before this PR, SharePlaceHolderWith share Tensor between different C++ Variable, which meas sharing the data, shape, and inplace_version_counter_ of Tensor.
But in some cases, Sharing data and inplace_version_counter_ but not sharing shape is needed. For example, inplace op reshape, can't share shape.

This PR, discard SharePlaceHolderWith, and expose ShareInplaceVersionCounterWith for C++ Tensor.
This reverts commit b10ecd9d.

* Support ShareInplaceVersionCounterWith to share the same inplace version counter for VarBase

* add topo aware

* resource.h

* topo aware

* format

* memory holder optimize

Change-Id: Ic91af8ac6f2853336d28a9fbbc5e8d0c57b5d05e

* memory holder optimize

Change-Id: I2fd1c14ecc17f5d5ce88b87890381ea801e6367f

* fix large scale memory holder

Change-Id: Ief0992b02b00220e16c72cc637a56e7b5788140f

* fix large scale memory holder

Change-Id: I910142a3952ead643a5604f8f80955f3e6efe655

* support deepcopy for Layer/Tensor/Paramerbase

* fix some code

* update, test=develop (#29559)

* Disable gloo by default (#29805)

* update, test=develop

* update, test=develop

* [Kunlun] PR1:Support one Kunlun card training in parallel executor (#29337)

* [Kunlun] PR2: Support MultiDevicePass and BKCL in parallel executor (#29574)

* [Kunlun] bug fix of PR2: Support MultiDevicePass and BKCL in parallel executor  (#29926)

* add bkcl.so in whl for kunlun (#29947)

* [Kunlun] bug fix of PR2: Support MultiDevicePass and BKCL in parallel executor  (#29961)
Co-authored-by: NQingshuChen <qingshu.chen714@gmail.com>

* [Complex] Add support for complex grad accumulated (#29889)

* add support for complex grad accumulated

* add unittest for coverage

* update test dtype

* remove useless blank line

* [Complex] Handle complex to real after type promotion (#29855)

* try to add fwd op input dtypes

* refactor base impl

* return tmp_ins after dygraph prepare data

* fix typo found in debug

* polish comment & add complex net test

* revert detail change

* fix unittest failed

* add complex kernel condition control

* fix xpu test failed & polish comment

* polish details by review comments

* Complex op test (#29753)

* delete no need to calculate inputs in dygraph op_test

* delete no need to calculate inputs in dygraph op_test

* change grad elementwise_mul for complex types (#29757)

* add conj op for complex types

* add conj for complex types

* add more test case

* add conj_op test

* modify conj api and impl

* add complex type for fill_constant_op xpu

* add setConstant for complex type

* remove complex conj test file

* user define grad for test_conj_op

* add test case for static mode of conj api

* modify conj doc

* change input args name to x

* remove useless codes

* conj support real types

* add conj test case for real number

* delete no need to calculate inputs in dygraph op_test

* delete no need to calculate inputs in dygraph op_test

* modify grad of mul for complex types

* fix the grads of inputs args order not match bug

* change the grad of div when complex types (#29804)

* change the grad of div when complex types

* fix the grads of inputs args order not match bug
Co-authored-by: Nchentianyu03 <chentianyu03@baidu.com>

* cherry pick heter ps

* 　CMakeList

* [Inference] FLAGS_call_statck is turned on default when ON_INFER=ON

* cherry-pick 29828

* support some shape in matmul and cast

* modify matmul

* [Dy2stat] Enable jit.save to Save Without Running (#29579)

Enable jit.save to Save Without Running.

* Modify CublasHandleHolder to Fix Random Unittest Failure. test=develop (#29617)

Modify CublasHandleHolder from using PADDLE_ENFORCE_CUDA_SUCCESS to PADDLE_RETRY_CUDA_SUCCESS to fix random unittest failure. We checked that the unittest log showed CUDA allocation error at this file, which may due to GPU not enough. We fixed similar failure in the past, so we applied PADDLE_RETRY_CUDA_SUCCESS here.

* feat: support check_nan_inf for kunlun device

* support kunlun stack

* minor

* add ps table (#29463)

* add ps table

Change-Id: I468a04bd071d21ff52654926fcf4d5f3da19e178

* add service (#29560)

* add service, remove ut on mac

* fix heter_profiler & add heter stop method

* fix code style

* merge pscore

Change-Id: Ie7f60d1cdde6755a0c29db26863c6283e9843d57

* fix cmake

Change-Id: I6773509a7b4ca79139ecc40b7bf3eb318ceff8bb

* fix conflit

Change-Id: I35575be0c96a8520f9d756ea7f1ff0b904a165ba

* fix conflit

Change-Id: Ic926ea0b0d67803226d51241397ba3b510226bfa

* add ps table (#29463)

* add ps table

Change-Id: I468a04bd071d21ff52654926fcf4d5f3da19e178

* add service (#29560)

* add service, remove ut on mac

* fix heter_profiler & add heter stop method

* fix code style

* add nearest_interp_v2 on kunlun

* add nearest_interp_v2 on kunlun
Co-authored-by: NTTerror <tangzhiyi11@users.noreply.github.com>

* fix fleet for multi-stream

* fix memcpy for ncclid

* use sync to solve move operation