use jinja 2.11.3 in python lower than 3.6.2

* perfect copy

* deal with conflict

* deal with conflict

* fix compile bugs

* fix unittest bugs

* change code format

* deal with conflict

* modify code by review

* fix ce bugs

* fix ce bugs

* add lo

* perfect code format

* deal with conflicts

* fix incompatible error

* rmeove default constructor

* add macro

* fix cpu make error

* add DefaultGPUPlace api

* Remove unnecessary including for pstring.h

* Fix typos

* move trace into api.yaml

* add trace unittest

* fix trace test

* fix generate op

* add codegen for get_expected_kernel, add argument mapping for selected_rows kernels, fix other bugs in codegen for operators.
* move bernoulli, erf, mv, poisson, trunc, erf to api.yaml and corresponding backward api to backward.yaml
* generate EmptyGradOpMaker for ops without grad op
* add code to generate all possible kernel signatures for infrt

* cpplint fix 3

* cpplint fix 3

* cpplint fix 3

* cpplint fix 3

resort .cu headers, set clang-format not sort include block and consider .cu as main source file (#43633)

* add new API/OP(csr->csr) of SparseTensor softmax

* fix comment

* fix to_sparse_csr

* [CustomKernel] add custom kernel c api

* update

* update

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

* fix xpu kp compilation

* add depends

* rename yaml file

* fix merge conflict

* fix infrt

* 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

* fix starganv2

* fix starganv2 stop_gradient end error

* fix edvr_starganv2

* fix mul kernel to fix optional ddx

* fix typo

* change logic for optimize

* modifty

* optimize the backward speed of EinsumOp

* add cache optimizer for einsum op

* EinsumOp: fix new dygraph mode error

* fix bug

* change Cache->InnerCache

* fix code

* fix

* add nan inf utils for einsum op

* add as_extra

* memory optimizer for einsum

* update code

* fix stride_slice bug

* fix bug

* use GpuMemcpy and GpuMemset

* sparse convert kernel support double dispatch by indices dtype

* cudaMemcpyKind->gpuMemcpyKind

* fix depthwise conv yaml error

* fix depthwise conv double grad error