* add o2 tune

* add unittest

* fix error

* set unittest timeout

* Add digamma, dirichlet tests

* Fix code

* add erf FP16 test

1. modify set_value op, use Scalars to represent attr `values`, instead of a bunch of attributs of various types; (#52408)

2. add program converter and set_value op as an example, which provides the functionality to convert `paddle::framework::ProgramDesc` between old and new formats(the differences are mainly some operators with incompatible updates in the definition);
3. program version and operator version map now are always saved when serializing `paddle::framework::ProgramDesc` to identify the version;
3. provide an option `legacy_format=false` in  serialization of `paddle::framework::ProgramDesc`, it decided whether to convert ProgramDesc back to a legacy format, which is compatible for paddle 2.4.2 or earlier versions to load and execute;
4. deserialization of `paddle::framework::ProgramDesc` is now automatically detecting whether the bytes it receives is in legacy format(contains any of the operators that has been incompatibly updated and have any attribute of type `Scalar`) and convert it to new format. But if you want a faithful deserialization without the automatic conversion, you can use protobuf's deserialization instead. Though it is not recommended, it can be used for the purpose of testing.

* add more infer var type

* fix split error

* fix ut

* fix top_k infer vartype

* fix top_k infer vartype

* support uint16 python op in d2s

* convert uint16 -> bfloat16 in docstring

* Unify the static amp codes of fp16 and bf16.

* Polish apis and add unittest.

* Add operator stats collecting tools for program.

* Add the check of number of bloat16 operators in unittest.

* Add warning for operator not supported for amp.

* Add testing of BF16 O1 and O2.

* Paddle-Trt: Replace fc mul matmul matmul_v2 with matrix_multiply

* No55 add channel_shuffle FP16/BF16 support and tests

* add_fp_bf_for_dot & bf_for_cross

* fix error

* fix some error

* fix some error

* change something

* fix magic number

* [AMP OP&Test] Support fp16&bf16 in reduce_max

* fix bilinear_interp_v2 && some other bugs in trt 7011

* add version check in test_trt_convert_bilinear_interp_v2.py

* Add GaussianNLLLoss API.

* Change `rotl` `atol`.Check `var` in dynamic graph

* remove assertTrue

* update unittest

* update unittest for ci-covarage.add broadcast with same dim.

* Supply static err print.

* Repair note and example.

* Split unitest.

* empty commit.

* for standard commit.

* for standard commit.

* Add int dynamic graph test.

* Repair parameters name.

* Repair unitest parameters name.

* Repair unitest parameters name

* Repair unitest parameters name

* Repair unitest parameters name

* add square in code-block

* fit few notes.

* fit few notes.

* fit few notes.

* fit few notes.

* add few interpretations.

* add few interpretations.

* add few interpretations.

* fix import.

* fix space.

* empty commit for ci.

* add auto parallel tuner options in launch

* add ut for launch in auto_parallel tuner

fix code format

* fix ci-converage

* adjust test_elementwise_sub's tolerance, max_relative_error of grad and
atol/rtol of output to 1e-3

* fix the dtype in setUp

* fix the elementwise_sub optest

* modify elementwise_sub optest

* fix and add bf16/fp16 to elementwise_sub

* fix elementwise_sub bugs

* fix bugs

* fix elementwise_sub op

* fix the data type

* fix elementwise_sub

* fix elementwise

* fix elementwise_sub

* fix bugs

* fix elementwise sub

* fix elementwise_sub

* remove scalar and vector

* Fix _param_grad_names when like 'param@GRAD@GRAD'

* [CINN] optest add cinn check test

* replace set self.check_cinn to pass check_cinn by function parameter

* fix ci bug

* add cinn atol/rtol

* fix bug in cross_entropy in static mode

* fix ci-coverage

* rem cncl in new test

* rem cncl in build sh

* rem cncl in old test

---------
Co-authored-by: NZhang Jun <ewalker@live.cn>

* [Auto Parallel] Speedup the completion process

* [Auto Parallel] Skip the property of dist_context when deepcopying

* [Auto Parallel] Remove the unnecessary print

* [Auto Parallel] Move some changes from 2.4 branch to develop

* Update engine.py

* [Auto Parallel] Fix a bug