cherry-pick for #18293

* Use TensorCopySync for sequence_unpad op

* Fix the tensor memory alloc bug

test=release/1.5

add dygraph api doc for fluidDoc and api spec

* fix slice op bug; test=develop

* fix variabel test bug; test=develop

* remove slice while true; test=develop

test=release/1.5

Repair error prompt: Users are prompted to check whether the model or parameter files are damaged when loading parameters are wrong.

* cherry pick 18000, test=release/1.5

test=release/1.5

* refine core cmake warning and print more info
* fix comments

test=release/1.5

* cherry-pick the inference update for win test=develop

* test=develop

* test=develop, add add_multi_gpu_install_check (#18157)

* test=develop, add add_multi_gpu_install_check

* test=develop, refine warning doc

* test=develop, refine warning doc

* test=develop, refine warning doc

* test=develop, support multi cpu

* test=release/1.5, cherry-picked from develop

* update some op doc, test=release/1.5

* fix relative import error in python3
* fix debug string info

* fix_create_lod_tensor, test=release/1.5

* remove program_guard import,test=release/1.5

* fix windows numpy default int32 error, test=release/1.5

* Update backward appending stragety to support double backward and fix some bug. (#18104)

* Update backward.py:
     - If there is no input grad var in all outputs of previous ops, do not append this op into graph.
     - Only apply this stragety when double backward.
* Update some double backward op.
* Update sum_op to judge whether a tensor is empty by numel or IsInitialized().

* add mkldnn Int8v2 slim doc (#17909)

* Change int8v2 CAPI unit test name and add log in the prediction stage (#18200)

* fix issue 18111;test=develop

* fix timer;test=develop

* refine code;test=develop

* test=release/1.5

* add multi process reader
test=release/1.5

* fix save/load in fleet (#17675)

* fix save/load in Fleet
* add UT framework of Fleet (#18058)

* add paddle cloud role maker for customized usage, note this is only for industrial users that have cloud environment pre-configuration (#18121)

add paddle cloud role maker for specific cloud usage. This pr will simplifies user's configuration in distributed training.

* assign role_maker before use (#18137)

* [Cherry-pick] change dirname mobilenet to mobilenetv1 (#18160)

test=release/1.5

* [Cherry-pick] update mkldnn int8v2 doc (#18177)

test=release/1.5

* cherry pick refine core warning message (#18063)

* cherry pick core replace x86cpu with py cpuinfo (#18151)

test=release/1.5

Cherry pick retinanet_target_assign_op(#17893), sigmoid_focal_loss_op(#17895) and retinanet_detection_output_op(#17896) for supporting retinanet (#18141)

* test=release/1.5
Fix conflicts in test_layers.py when adding target assign operator for supporting retinanet. Cherry pick #17893

* test=release/1.5
Add sigmoid focal loss operator for supporting retinanet. Cherry pick #17895

* test=release/1.5
Add detection output operator for supporting retinanet. Cherry pick #17896

* test=release/1.5
fix wrong code style in test_layers.py when cherry pick retinanet_target_assign #17893

* test=release/1.5
Fix type error of std::pow in sigmoid_focal_loss. Cherry pick #17895

* fix logging unable. test=develop

* unset sys.stdout for stream handler. test=develop

* fix newly add basicConfig. test=develop

* fix import error. test=release/1.5

* update execution_strategy option default value
test=release/1.5

* fix doc error
test=release/1.5

* remove nccl dep when the number of GPU is 1
test=develop

* use multi card run syncBN
test=release/1.5

Add trainer_desc proto DEPS to solve CI random fail.

Add cascade rcnn support.

Cherry pick #18077 and  #18111 unify FP32 vs. INT8 comparison tests output, reuse C-API INT8 unit test application (#18145)

* unify FP32 vs. INT8 comparison tests output (#18111)

test=release/1.5

* reuse C-API INT8 unit test application (#18077)

test=release/1.5

* fix get items slice bug; test=develop

* fix unique_name bug; test=develop

* fix dygraph mem leak, test=release/1.5

* polish msg, test=release/1.5

cherry pick for deform roi pooling

* add UserDefinedCollectiveRoleMaker for collective mode (#17898)

cherry-pick for (https://github.com/PaddlePaddle/Paddle/pull/17402)

Add Pipeline Concurrency Train Mode:
- Cpp: pipeline_trainer & section_worker
- Python: PipelineOptimizer
- Add a new data_feed type: PrivateInstantDataFeed
- Add a test demo of pipeline trainer and the test model is gnn
- Do not support win32 now

cherry pick requirements update
pr: 18123
pr: 18068

* fix multithreading issue

test=develop

* rview fixes

test=develop

* reivew fix: omp->cpu, infernce_api.cc->pybind.cc

test=release/1.5

* fix py_reader iterable bug, test=release/1.5

* move data from buffered_reader,test=release/1.5

* update CPU_NUM config
test=develop

test=release/1.5
cherry-pick from #17952
The scatter op has a calc bug when the indices has same index, the scatter op use overwrite mode to calculate the same index, fix this bug by using the accumulate mode to calculate the same index.At the same time, the gather op has the same bug when the op calc the grad. And we use the lib of open-blas and eigen to optimize the time cost in accumulate mode.