* add CPUDeiveEvent

* Polish DeviceEvent code

* Add DEVICE_EVENT_LIBS

[oneDNN] disable caching oneDNN primitives in  matmul v2, Reduce grad and elementwise_add grad, expand_v2 (#35132)

* - grad caching disabled of matmul_v1

- compilation fix

- compilation fix

* - reduction removed

* - Matmul v2 disabled caching

* Draft of further changes

* - workaround for reducegrad

* - fixes to UT

* - fix to compilation

* - another fix

* - fix

* add device_context

* add gtest for device_event_gpu

* Remvoe duplicate DeviceType

* push for test

* add unittest

* fix macros

* fix MSVC using usage

* Add function to disable paddle signal handler

Paddle used google::InstallFaultSignalHandler to handle selected system signals,
mainly for debugging and bug report purposes.

However, this can be conflicted with other python packages whoever captures similar signals.
Such python package involves tvm and more

To resolve this issue, we support a function to disable signal handler

* Remove signal test from WIN32 platform

* Remove redundant return from disable_signal_handler() function

* Add detailed messages to en_doc

* copy boost optional.hpp to paddle

* copy boost optional.hpp to paddle

* move directions

* del fluid/utils

* modify .hpp to .h

* move directions

* modify to paddle::optional

* add modification description

* format code stype for the files in paddle/utils

* format code stype

* - disabled caching of layer norm

- fix in compilation

- compilation fix

- transpose caching disabled

- compilation fix

- more compilation fixes

- sum caching disabled

- compilation fix

* - LRN with disabled cache

* lint fixes

* - Added softmax without caching

* - Binary is no longer manually cached

* - Activation onednn caching removed

* - Removed manual caching of activation

* - modified UT

* - fix

* - fix

* - fixes to building

* - fix

* - fix

* - fix to UT

* - Faulty UT workaround

* - approval workaround

* - Fixes after review

* - compilation fixes

* - more lint fixes

* - more fixes after review

* - fixes after another round of review

* - hopefully compilation fix

- compilation fix

* OP dot: refactor CPU kernels and get better loop performance.

* Minor fix on code format.

* Fixed minor errors.

* Add new API: einsum

* Update the Einsum unit test.

One case failed with matmul_v2, where the dtype is int64:

a = np.arange(2 * 3 * 1).reshape(2, 3, 1)
b = np.arange(1)
paddle.einsum("...i, ...i", a, b)

* Test cases in test_einsum test floating point dtypes only.

As of now Paddle only supports float/double dtypes in matmul, which is
one of building blocks of this Einsum implementation. We decide not to
test einsum against other dtypes.

* Polish format.

* More formatting.

* Format...

* Einsum: improve test coverage.

* Einsum: bug fixes and more testcases for testing error messages

* Einsum: fix format..

* Einsum: fixed typo and format.

* Einsum: format again...

* Einsum: applied suggested changes.

* Einsum API: improve API documentation.

* Einsum API: apply suggested changes.

* Einsum API: Add dygraph only note.

* Einsum API: Add dygraph only note.

* Einsum API: fixed unittest.

* remove unmatched signal error stack

* fix error writing for cond

This reverts commit 0a5c99e8.

* - Added softmax without caching

* - Binary is no longer manually cached

* - Activation onednn caching removed

* - Removed manual caching of activation

* - modified UT

* - fix

* - fix

* - fixes to building

* - fix

* - fix

* - fix to UT

* - Faulty UT workaround

* - approval workaround

* - Fixes after review

* - compilation fixes

* - more lint fixes

* - more fixes after review

* - fixes after another round of review

This reverts commit 090c863a.

* support kunlun black list and add kl1 op

* xpu_op_list add device_context dependence

* replace boost::algorithm::ends_with with self define ends_with function

* remove BOOST macro in certain operators

* remove boost::lexical_cast

* add test for string_helper

* add more test case for string_helper

* modify join_string func and test case

* fix build_strategy_test failed bug

* remove string_helper_test from parallel_UT_rule.py

* support Kunlun2

* support KL2

* support KL2

* added expand_v2 bf16/fp32 kernel

* minor change

* CI fix

* added missing test file

* added formatting

* reduced binary size

* CI fix

* add fix op run order pass

* add ut for fix_op_run_order

* fix ci error

* improve coverage

* improve coverge again and fix cpu test case

* follow some comments

* fix cast

* 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

* Refine Constructor logic of ParallelExecutor

* Replace executor into ParallelExecutor in run_program_op

* - fix to #33282

* - Increased threshold for elementwise_mul_bf16 grad

* -disabled faulty UT

* - fix to approval

* Modify the search order of dynamic library

* Modify the search order of dynamic library

* base changes for split op

* 90% of split functionality added

* full fp32 functionality

* added bf16 test

* added submemory caching

* added bf test to static mode whitelist

* minor change

* enabled split op for inference

* minor fix

* minor fix

* enable npu alignment

* support flatten_params/grads

* support clip by global norm

* remove memset in coalesce_tensor_op

* fix npu kernel of sum op when input is one tensor

* add ut for flatten_param_grads+regularizer

* fix ut

* fix typo