* refine squeeze, test=develop

* update squeeze, test=develop

* refine compile-time infershape, test=develop

* add more unittest, test=develop

* follow comments, test=develop

* add update_api, test=develop

* follow comments, test=develop

test=develop

* New features, add sinh and cosh op, test=develop

* remove duplicate test function and remove out paramters, test=develop

* Add out paramters temporary, remove later. test=develop

* remove out args, PR 25570, test=develop

* remove TestParameter, test=developx

* add test api for static dygraph, test=develop

* add backword unittests for sinh and cosh, test=develop

add fp64 support in sequence_pool, test=develop

Fix the condition of concat dimension judgment.

* update ResetHolder, test=develop

* add TensorShare for lite engine, test=develop

* tensor data changed from copying to sharing, test=develop

* supports xpu runtime, test=develop

* fix code styles, test=develop

* add reinforcement learning model test=develop

* align backward test=develop

* add gym in paddle_build.sh test=develop

* rm pip install in script test=develop

* refine paddle_build.sh test=develop

* fix sed error in macOS test=develop

* polish code test=develop

* fix scope problem

* refine code by reviewer comment

Add Support for SelectedRows for Transpose OP and Fix a Bug That SelectedRows Cannot be Supported in SimNet (#25536)

This PR fixes a bug that SelectedRows cannot be supported in SimNet. The reason of this bug is that dygraph basic_engine didn't copy var's type when the var needs to be accumulated during backward. So when a var is SelectedRows and needs to be accumulated, like SimNet which calls net for two times, the var's type will be changed to default LoDTensor thus bug happens. To fix it, we just also copy the type.

Without this PR, the accumulated SelectedRows parameters in dygraph will be changed into LoDTensor. So when we fixed the bug of supporting SelectedRows in SimNet, we found `test_imperative_lod_tensor_to_selected_rows` failed and threw the error that SelectedRows was not supported for Transpose OP. To fix it, too, this PR also added support for SelectedRows for Transpose OP.

* fix doc of logical_* op.

* fix doc of op pow.

* fix comment syntax error9D

* fix operator reciprocal demo.

* fix logical_* ops' doc. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* bug fix. test=develop,test=document_fix

* fix topk_avg_pool hang test=develop

* refactor get_topk_pos test=develop

* add check of channel_num and num_k test=develop

* add TopKPosPaddingId test=develop

* add bilateral slice op

According to paddle 2.0 standard
1, change flip api attr name 'dim' to 'axis'.
2, support empty axis
3, change example code to imperative mode.

* experimental refactoring, test=develop

* add TranslatedLayer & remove StaticModelRunner, test=develop

* revert tracedlayer change, test=develop

* fix test_mnist unittest error, test=develop

* add doc & examples, test=develop

* polish doc details, test=develop

* add imperative.jit module, test=develop

* change TranslatedLayer pos, test=develop

* adjust jit module import path, test=develop

* polish doc based review result

* add SaveLoadConfig.separate_params to save paraams separately

* add Layer.buffer support, test=develop

* polish doc details based review result, test=develop

* polish details baesd review comments, test=develop

* add empty str check for param, test=develop

* add unittests, test=develop

* polish details based review comment, test=develop

* remove blanks in comment, test=develop

* polish doc details, test=develop

* update imperative doc link, test=develop

* add api attr for load, test=develop

Add Similarity Net as unit test. During the unit test, we found three problems:

1. The run_program_op has memory optimization error when running dy2stat net multiple times.
2. The support for SelectedRows can cause problem in dy2stat.
3. The return grammar has problem.

This PR fixes the 1. problem but modify codes for the 2. 3. problems to make PR smaller. I will fix those two problems in the next PR(s)

* Add the imperative quantization aware training.
*  This is the python part of Imperative QAT. test=develop

* fix softmax_with_cross_entropy cuda kernel overflow bug, test=develop

* replace old macro & for condition, test=develop

* polish details, test=develop

* add explicit specialization

* add skiplayernorm vector load if available

* test=develop

* fix concat shape error
test=develop

* add retry for prefetch

* Revert "Fix/sync barrier (#25016)"

This reverts commit be6a315f.

* reopen dist UT, test=develop

* remove fl UT, test=develop

* fix bn & in in dy, test=develop

* update instance_norm,test=develop

* fix bugs,test=develop

* add more case in unittest,test=develop

* fix,test=develop

* fix,test=develop