* [Auto Parallel] Rename methods of ProcessMesh

* [Auto Parallel] Impl the python process_mesh by the c++ one

* [Auto Parallel] Add some minor modifications

* [Auto Parallel] Rename some methods

* [Auto Parallel] Remove unnecessary codes

* [Auto Parallel] Add back some removed files

* [Auto Parallel] Fix bugs

* [Auto Parallel] Fix a bug

* Update process_mesh.cc

* [Auto Parallel] Merge dist attrs of Python into C++

* [Auto Parallel] Add back deleted importing

* [Auto Parallel] Add back removed unittest

* [Auto Parallel] Remove type qualifiers of return types

* [Auto Parallel] Fix some bugs

* [Auto Parallel] Fix a bug of the quant pass

* [Auto Parallel] Fix the code style

sequence_mask fix: when the input length is an empty tensor, the kernel tries to dereference illegal sentinel iterator (#49525)

* support 0D for paddle.sort/argsort

* support 0D tensor for paddle.sort/argsort in xpu

* fix bug

* fix grad and add value assertion

* generate the static graph code of ops

* modify the isclose comment

* modify the clip comment in nn.py

* reset nn.py

* update nearest_interp, expand_v2, cast for stable diffusion

* update nearest_interp, expand_v2, cast for stable diffusion

* correct shape rank

* Update expand_v2_op.cc

* CINN add fetch op for skip gc vars

* perfect test annotation

* break if not is_only_used_internal

* move skip_gc_var_names get out of for loop

* rm op_function_generator

* rm op_func_generator.h

* rm op_function

* modify cmake

* rm op_function.h

* rm check for op_function_generator.cc

* reset imperative

* rm python part

* fix imperative

* lint

* lint

* modify legacy_c

* review

* modify

* modify legacy

* rm gen op_functions code

* reset framework

* rm core.ops for test

* core.ops->core.eager.ops.legacy

* not raiseError for xpu

* refactor: use base class

* fix: incorrect deps

* fix: add missing header

* refactor: update class structures

* fix: bkcl typo

* fix: remove redundant def

* delivery skip_gc_vars from the main graph to each subgraph compiled by CINN

* rearrange format and annotation

* fix lacking namespace

* fix segmentation fault cinn subgraph doesn't own kSkipGcVarNames

* deliver all skip_gc_vars of main graph

* add vlog for skip_gc_vars

* modify setup.py and paddle_build.sh

* modify setup.py and paddle_build.sh

* modify setup.py and paddle_build.sh

* modify setup.py

* modify run_setup

* modify setup.py

* fix make_clean

* modify setup.py

* modify setup.py

* delete setting python_libary

* debug

* debug

* debug

* debug

This reverts commit 2c444dfa.

* execute use kernel_key first

* change OpKernelType->KernelKey

* fix py3 compile error, remove redundant header files

* fix build_strategy_test

* fix DataType::RAW

* fix custom_type test: operator_test.cc

* fix transform place

* fix backends_are_same_class

* try fix place TransDataDevice

* support all KernelKey

* fix TransformData

* fix place_are_same_class

* fix merge

* fix test_params_no_grad

* fix specific place of GetExpectedKernelType

* fix specific place of GetExpectedKernelType

* fix GetKernelTypeForVar

* fix dtype error

* fix fetch_v2

* change GetKernelTypeForVar

* fix interpreter

* fix typo error

* polish codes

* polish codes

* polish codes

* fix conflict

* Fix param and out grad names in dy2st for high order grad

* replace matmul with matmul_v2 in fuse passes

* Remove fusion logic from matmul

* removing fusion methods

* add proper name

* adjust namespaces

* Implement conv2d_fusion NHWC format using CUTLASS
* Add unit testing for CUTLASS Conv in inference
* Add experimental API for CUTLASS.

* [OpAttr]Fix Ignore AttriteTensor in IndicateDataType bug in grad_op

* add GetExpectedKernelType

* Use BroadcastKernel and ReduceKernel to optimize expand and expand_grad.

* Correct the axis when there is only 1 input in BroadcastKernel.

* Add the calculate of output's shape.