* [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

* add pool flops

* add annotations and tests

* 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

* [Eager] optimize same python api logic

* optimize full api

* optimize logic

* optimize logic

Add 0d Tensor Test Cases for cond, case, switch_case. Since the 3 APIs are control flow APIs, their support for 0d tensor relies on the underneath APIs. This PR just added test cases to prove that the 3 APIs have already handled 0d tensor well.

* remove deps and prior comm

* grad comm fuse

* add deps for amp&global norm

* stage2 broadcast prior deps

* stage2 grad overlap

* stream_analyzer bugfix

* overlap enable

* dep op namescope

* depend support multiple inputs

* check finite deps

* stage2 param comm overlap

* Set kD2HStream

* grad comm hierarchical

* grad comm hierarchical

* new unitest
Co-authored-by: Nchenruibiao <chenruibiao@baidu.com>

* update requirements.txt and setup.py.in

* update requirements.txt setup.py.in setup.py

This reverts commit 2c444dfa.

* add for-else

* add * for unpacking

* [CodeStyle][isort][UP019] sort imports and update deprecated type annotation in paddle/jit/api.py

* Revert "[CodeStyle][isort][UP019] sort imports and update deprecated type annotation in paddle/jit/api.py"

This reverts commit 0ca4d52c900199126e6433057d1514dbf9d4ee07.

* update deprecated typing

* 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

* move fc from fluid to paddle2.0

* fix unit test

* fix some examples

* fix some examples

* remove fluid.save_dygraph and fluid.load_dygraph use paddle.save and paddle.load instead

* move Sequential to paddle.nn

* modify convert_call_func.py Sequential reference

* remove related unitests

* remove fluid.dynamic.Sequntial

* test remove conver_call_func

* fix conflicts

* fix typro

* fix unitests

* fix sample_code

* fix unitest

* fix __init__

* 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