* reduce_mean supported. test=allcase

* ut. test=allcase

* test=develop

* ut.test=allcase

* correct name. test=allcase

* correct UT. test=allcase

* correct UT.test=develop

* remove op

* UT

* add convert

* fix timeout issue

* more uts

* more ut

* correct ut

* fix cast

* add trt noexcept definition

* add trt noexcept on trt plugin

* add trt noexcept on trt int8 calibrator

* remove noexcept on base serialize

* add trt noexcept on split plugin

* add trt noexcept on elementwise plugin

* add trt noexcept on prelu plugin

* add trt noexcept on pool plugin

* add trt noexcept on swish plugin

* add trt noexcept on gelu plugin

* add trt noexcept on layer norm plugin

* add trt noexcept on instance norm plugin

* add trt noexcept on emb eltwise layernorm plugin

* add trt noexcept on qkv2context plugin

* add trt noexcept on skip layernorm plugin

* add trt noexcept on slice plugin

* add trt noexcept on hard swish plugin

* add trt noexcept on stack plugin

* add trt noexcept on special slice plugin

* add trt noexcept on anchor generator plugin

* add trt noexcept on yolobox plugin

* add trt noexcept on roi align plugin

* add trt noexcept on gather nd plugin

Add boost as dependency to fix random compilation failure. This is due to program_processing.cc used boost but didn't write boost into DEPS in the CMakeLists.txt

* change strided_slice when step<0.

* add unittest for paddle.strided_slice

* polish unittest

* add cuda event and stream api

* add cuda event and stream api

* add get_current_stream api

* add get_current_stream api

* init streams

* modify get_current_stream

* modify get_cuttent_stream

* add synchronize func

* add current_stream doc and test file

* move get_current_stream into CUDA macro

* move CudaEvent into CUDA macro

* move _get_current_stream and _device_synchronize into cuda macro

* modify the macro of cuda stream and event

* add test case for synchronize

* add paddle.devices.cuda module

* event and stream support hip

* add doc for stream and event class

* move cuda stream and event into single pybind

* add cuda_streams_py.cc to cmakelist

* add _device_synchronize and _get_current_stream to core module

* add test case for cudastream and cudaevent

* move __all__ in streams.py

* fix test fail

* add cuda to devices __all__

* fix current_stream doc writing error

* move devices to device direction, and merge device.py into __init__.py

* add required:gpu to sample codes

* remove cuda direction from device/__init__.py

* add wait_server_ready

* fix remove bug

* [NPU] add sigmoid and sigmoid_cross_entropy_with_logits

* [NPU] add debug logs

* [NPU] delete debug logs

* [NPU] reset to paddle.NPUPlace(0)

* [NPU] add more unittests for sigmoid_cross_entropy_with_logits

* delete useless c++ code, and delete check_dygraph=False

* [NPU] delete repeated codes of unittests

* [NPU] fix licence code style

* [NPU] add attrs (now do not support) check for sigmoid_cross_entropy_with_logits

As the title, this PR converts all blocks in program into SSA sub graphs and it is guarded by flag

* add clear_float_status op

* refine infershape

* fix typo

* refine check_finite_and_scale

* refine code

* Add NoNeedBufferVarsInferer

* fix code style

* fix bn

* fix

* add unittest

* fix cpu

This PR creates a class to process the program at the C++ level. Currently, this class has one class method:
GetInputsOutputsInBlock()

* Add DCU backend support for custom ops

* Added checks for DeviceCopy and renamed some macros

[pass enhance] make the attribute check only object to which defined in op proto. test=develop (#34146)

* Refine Constructor logic of ParallelExecutor

* Replace executor into ParallelExecutor in run_program_op

* add scatter-gather opt

* fix topo for pp

* rename function

* adam add input SkipUpdate

* add unittest

* add npu unittest

* fix xpu compile

* remove param stream

* Support sccache to speed up compilation on Windows

* Support sccache to speed up compilation on Windows