* oneps (3/4)
Co-authored-by: NMrChengmo <cmchengmo@163.com>
Co-authored-by: Nmalin10 <malin10@baidu.com>
Co-authored-by: Nchengmo <chengmo@baidu.com>

* support Baidu AI Accelerator
  * test=kunlun

* minor
 * test=kunlun

* support xpu op in separate file
 * test=kunlun

* update XPU error message and remove duplicated code

 * test=kunlun

* minor
 * test=kunlun

* minor
 * test=kunlun

* Added DNNL cache management for DyGraph

* move FLAGS_use_mkldnn to more general CMakeLists, getu use of the flag in ClearGradients

* missing file

* Fixes after review

* Bringing back original idea of place for 'use_mkldnn' flag to be accessible from platform nad imperative.

* Removed duplicate and added docs

* Fixes for CI

test=develop

* add new macro BOOST_GET_SAFELY & unittests, test=develop

* add different macro type, test=develop

* fix get macro type in executor, test=develop

* four macro part change backup

* using one macro for all case, test=develop

* revert attribute change, test=develop

* change to three func to solve gcc4.8 bug, test=develop

* polish some details, test=develop

* Support LoDTEnsorArray in fetch op

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

* Support LoDTensorArray in fetch

test=develop

This PR enhances error messages of several API/OPs:

ParallelExecutor (python && C++)
Executor (python && C++)
StaticRNN (python)
IfElse (python)
cond (python)
split_lod_tensor (python && C++)

* Remove the NGraph engine from PDPD repository
1. Each operator was removed from the operator's directory
2. Each test was removed from the unittest directory
3. The parallel executor support was removed from the PDPD
4. The CMake file was removed from the PDPD
5. The NG flags were removed from the repository
test=develop

* Remove ngraph from:
1. Cmake file
2. Python file
test=develop

* static model runner basic implement, test=develop

* add run program op to execute loaded program, test=develop

* refactor static model runner & run program op, test=develop

* reset engine.cc to resolve conflict

* adapt the change of dygraph double grad, test=develop

* refactor impl to solve control flow error, test=develop

* clear debug code, test=develop

* fix ci str compatible error & checkout dygraph grad maker & add example, test=develop

* hide api & add op test, test=develop

* fix run program op test places error, test=develop

* fix program by review comment, test=develop

* delete change var desc name, test=develop

* fix other program by review comment, test=develop

* remove _static_graph_guard, test=develop

* add selectedrows test, test=develop

* remove desc parser, test=develop

* fix detail program, test=develop

* change socpe create & add test, test=develop

* Commit before merging develop

test=develop

* Backup after working with Huihuang logs

* Commit before deleting Huihuang debug loggings

* Commit before debug

test=develop

* Fix bug commit

test=develop

* Backup of fixing bugs

test=develop

* Clean up code

test=develop

* Fix a bug in sum_op

test=develop

* fix fetch handler problem and refactor
when a user define FetchHandler class, he or she should initialize a handler
with variable dict. the key of a variable dict is a user defined name,
the value of a variable dict is a Varaible generated from python API.

For each fetching, a user should implement handler function in which
fetched_result_dict will be available and the user can access the fetched value
with user defined keys.

* Refine the cache of program, context and scope in executor.
test=develop

* Refine the unittest test_executor_and_use_program_cache.

* Add the test the PaddingRNN with use_program_cache=True.
test=develop

* Remove a check.
test=develop

* Refine the unittest to check whether it is correct when setting use_program_cache=True.
test=develop

* - Flushing mkl-dnn cache

test=develop

- Disabled clearing cache for LoadModel

- Added clearing of mkl-dnn cache when Executor is created

test=develop

- Do not clear for GPU places

test=develop

- compilation fix

test=develop

* - Moved clearing of mkl-dnn cache in destructor of executor

test=develop

* - Compilation fix

test=develop

- Reverted conditional clearing of mkl-dnn cache in Executors's
  destructor

test=develop

- compilation fix

add executor.FetchHandler for train/infer from the dataset

* enable ngraph throught build_strategy test=develop

* add unittest test=develop

* put use_ngraph unconditional test=develop

* remove paddle_enforce test=develop

* remove paddle_enforce test=develop

* fix copyright test=develop

* limit for ngraph only test=develop

* open gc by default, test=develop

* fix test_train_recognize_digits and disable gc when ngraph is enabled, test=develop

* fix conditional_block op eager deletion bug, test=develop

* add some comments to reviewers, test=develop

Test PaddingRNN on V100 GPU device.

Test configuration: large model, padding mode (which is the mode using recurrentOp), one GPU.
                   
GPU memory (MiB):   6414 (this PR)     vs   6837 (without this PR)
Speed (steps/s):         10.28 (this PR)    vs    9.89 (without this PR)
 

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

* delay infershape test=develop

* fall back subblock to paddle test=develop

* fix edge cases test=develop

* remove output duplicates test=develop

* handle reshape2_grad infershape test=develop

* fix prepare context redundant code problem, optimize executor by caching create_varaiables
test=develop

* cache sub_scope, program, var when use_program_cache=True is set

* make fetch_list runable with variables, add more unittest for use_program_cache

* polish_executor_and_add_ctx_cache

test=develop

refine gc code
test=develop

* remove concast_cast and refactor code test=develop

* reduce flag use test=develop

test=develop

test=develop

test=develop