* add align for WorkQueue

* add spinlock

* merge develop

* merge

* Add EventsWaiter

* Revert "Add EventsWaiter"

This reverts commit e206173aa9be7401b83a53581627bfaf557c8fb2.

* split template

* Add Profiler and HostTracer

* update

* update

* update

* updateg

* fix cmake
Co-authored-by: Nliutiexing <liutiexing@google.com>

* add align for WorkQueue

* add spinlock

* merge develop

* merge

* Add EventsWaiter

* Revert "Add EventsWaiter"

This reverts commit e206173aa9be7401b83a53581627bfaf557c8fb2.

* Set thread name for WorkQueue
Co-authored-by: Nliutiexing <liutiexing@google.com>

* refactor scale kernel that its input is selected_rows

* complement upload file

* move digamma to pten; test=develop

* fix mutable_data bugs; test=develop

* remove useless code; test=develop

* remove kernel compute; test=develop

* fix bug; test=develop

* slice

* shuffle pass enhancement

* [PSLIB] Add Metrics Module, Support User-defined Add Metric

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI Coverage

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI

* [PSLIB] Modify According to CI Coverage

* [PSLIB] Modify According to CI Coverage

* [PSLIB] Modify According to CI Coverage

* modify role_maker

* update CMakeLists.txt

* remove remake densetensor

* fix eager test error

* fix bug in eager

* implement AllocateFrom

* remove WriteBackOutput

* fix problem of eager
Co-authored-by: Nzkh2016 <zhangkaihuo@baidu.com>

* Refactor TensorAdd func by template and remove gradient_accumulation in eager

* Remove needless target name

* Use overload instead of template

* implement AllocateFrom

* fix PR-CI-Coverage timeout in 120s
Co-authored-by: Nzkh2016 <zhangkaihuo@baidu.com>

* add the test case for the UVA

* add the context load for the uva

* Add graph_sample kernel

* Add graph_sample commit

* add new commit for graph_sample

* add unsigned long long int

* delete some remarks

* add cpu version

* add cuda eids

* add cpu eids

* delete _uva

* optimize speed: emplace_back, last_layer

* add to_uva_tensor

* add cpu return_eids choice

* add gpu return_eids choice

* add cpu reindex_nodes

* add gpu reindex_nodes

* rename op and add OMP for cpu

* add incubate api

* fix the compile problem for the PADDLE_ENFORE and different device

* fix the rcom and windows compile problem

* add unittest for graph_sample_neighbors

* fix cpu unittest and unique problem

* fix uva unittest, fix cuda unique problem

* fix the windows compile problem

* fix the windows rand_r compile problem

* add correct unittest, add src_eids dispensable

* delete black

* combine uva unittest

* mv Sample_index to Sample_Index; check input shape; fix random sample func

* delete memset & cudaMemset

* fix according to PR comments

* fix rocm ci

* modify function names according to the specification

* fix windows_openblas ci

* refine annotations, fix windows unittest, add default value for uva device_id, fix bug for input nodes with empty neighbors

* fix rocm ci

* rename graph_sample_neighbors as graph_khop_sampler, add incubate api doc

* add data type

* fix conflict
Co-authored-by: Nwawltor <fangzeyang0904@hotmail.com>

* add constructor for win

* change impl

* fix bug

* remove remake densetensor

* fix eager test error

* fix bug in eager

* Support allocate_from in Tensor and allocate_data in Context

* fix #ifdef CUDA

* fix cycle depends

* fix test_xxx_dev_api failed

* fix windows compiling error

* fix unittest

* modify into PImpl

* fix selected rows

* add TODO comment

* refine interface according reviewer

* add infermeta registry

* add infermeta registry

* add unittest

* polish details

* [Demo] custom kernel based on pten kernel

* merge and npu custom work well

* del comments

* delete other code

* fix CUDAContext

* fix not found small_vector.h

* support NPU

* fix NPUContext

* fix DeviceContext support

* add UT

* fix call

* add UT

* fix

* fix for comments and ut

* add MACRO control

* fix multi input output

* support env CUSTOM_DEVICE_ROOT

* deal with special cases

* fix for Windows

* try coverage with test_custom_kernel_dot.py

* fix test_custom_kernel_dot

* fix test_custom_kernel_dot

* fix merge

* fix merge

* fix CI

* update

* merge and fix

* remove WITH_CUSTOM_KERNEL

* fix merge

* merge and fix

* fix ut

* fix ut for mac

* add more UT

* add more UT

* fix

* Upadate pass in quant2_int8_mkldnn_pass

* Back to the previous scale_matmul order

* Change place of cpu_quantize_placement_pass

* add full_kernel xpu

* fix full xpu register device type error

* fix full kernel bug

* add fulllike kernel impl and replace with raw kernel

* fix dev_ctx convert template args error

* modify namespace and header file

* add isinf check

* fix input type args in TensorSetConstantXPU error

* shuffle channel pass

* add ut

* timeout fix

* makefile fix

* update planner

* update unitest

* update dist matmul

* update auto converter

* optimize kunlun/xpu softmax_with_cross_entropy add add unitest
*test=kunlun

* minor
*test=kunlun

* minor
*test=kunlun

* minor
*test=kunlun

* minor
*test=kunlun

* fix slice bug

* fix syntax error

* compile for afs api

* with pslib

* fix bug:
1. atten: set the default value of attn_dropout_rate to None
2. ffn: add activation parameter

* for pure fp16

* Add a SparseCsrTensor

* remove unused functional

* remove const

* remove SetMemoberTensor

* remove non_zero_nums_, the number of non zero elements of each batch can be obtained from the crows

* SparseCooTensor

* add SetMember

* merge upstream; add SetMember

* merge upstream

* merge upstream; add newline at end of file

* add newline at end of file

* remove newline at end of file

* remove newline at end of file

* stash

* user pten::framework::make_ddim

* user pten::framework::make_ddim

* merge upstream; use the latest mutable_data

* merge upstream; use the latest mutable_data

* return mutable dense tensor

* update dist param grad for pass

* update unitest

* update unitests

* fix conflict

* Paddle-Inference:fix_concat_slice

* Paddle-Inference:fix_concat_slice

* Paddle-Inference:fix_concat_slice

* Paddle-Inference:fix_concat_slice

* [Paddle-Inference]: fix concat slice

* [Paddle-Inference]: fix concat slice

* [Paddle-Inference]: fix concat slice

Support the cases that the indices shape size is larger than the arr shape size

* add master weight for opt state_dict

* check empty of master weight

* strict gpu test

* refine unittest