* refine cmake of framework

* add deps for dense tensor

* fix deps

* remove alloc(ctx)

* add depends on mkldnn

* 【Hackathon No.34】优化 poisson op

* [poisson] code style fix

* modify code style

* prevent from big number

* modify code style

* modify code style

* modify import

* modify import

* modify code style

* [CustomDevice] add profiler apis

* migrate CalculateEstOccupancy into cuda_tracer

* update

* add ut

* change to async mode for xpu multi-card training in static graph mode

* minor bugfix

* irrelevant. move to another pr

* move change to other pr

* fix stream issue

* fix 'stream not meet with current context' error

* fix branch diverge, test=kunlun

* add macro control in enforce_xpu.h, test=kunlun

* minor bugfix

* minor bugfix

* set cuda device before run

* add header file

* fix compile

* infer context fix place error.

* update

* update

* init

* move CUDAStream to phi

* fix compilation

* merge develop

* add stream_owned_ member

* split cuda_stream.h

* fix cpu compile

* fix constructor

* fix bug

* fix windows compile

* fix inference test_levit

* fix windows tests

* multi stream support handle lazy init.

* support eigen lazy init

* update

* fix ci problem

* compile into one static library

* fix xpu compile

* fix xpu compile

* fix inference compile

* fix inference compile

* add custom test

* revert one file

* update xccl lib
    * use separate streams for compute/comm on XPU
    * add broadcast op to xpu2_op_list

* adapt mkldnn kernel in PHI

* fix ci compile bugs

* fix compile bugs

* fix compile bugs

* fix compile bugs

* fix compile bugs

* delete comment

* fix compile bugs in windows-inference

* delete code for converage

* modify code by review

* modify code by review

* add todo

* fix compile bugs

* fix compile bugs

* fix compile bugs

* fix unittest bugsx

* [CustomDevice] add custom ccl api

* add ut

* [CustomKernel] add capi eager mode support

* add ut

* add capi test

* clean glog header in public header

* move marco pos

* Dataloader add custom device support

* update test=document_fix

* unify cpu context

* fix init()

* delete test_device_context

* fix test_scalar

* [Sparse]add SparseTensor mv kernel(csr*dense_vec->dence_vec, coo*dense_vec->dense_vec)

* fix CI

* [CustomKernel] add custom kernel c api

* update

* update

* fix unable to export capi
Co-authored-by: Nronny1996 <524019753@qq.com>

* add some kernel(csr*dense->csr, dense*dense->csr) of SparseTensor matmul

* fix CI

* fix CI

* fix comment

* fix comment

Use int64_t in GetGpuLaunchConfig1D and ElementwiseKernel as index type to support large tensor. (#43506)

* Change some data type from int to int64_t in GetGpuLaunchConfig1D to support large tensor.

* Use int64_t in ElementwiseKernel as index type to support large tensor.

* Refactor port.h

* Remove some unnecessary code

* Fix CI errors

* use GpuMemcpy and GpuMemset

* sparse convert kernel support double dispatch by indices dtype

* cudaMemcpyKind->gpuMemcpyKind