cudaStreamSynchronize randomly hang when used in multi-thread environment, replace it with cudaStreamQuery API on windows

* simplify C++ error stack by rewrite Place, test=develop

* polish assignment overload func, test=develop

* delete paddle infershape enforce marco (#20832)

* Polish and arrange code in enforce.h (#20901)

* Enrich the type of error and declare the error type interfaces (#21024)

* Enrich the type of error and declare the error type interfaces, test=develop

* adjust tests to adapt new form, test=develop

* add inference deps with error_codes.pb.h, test=develop

* restore stack iter start pos, test=develop

* polish code based review comments, test=develop

* Add dependency for error_codes.proto (#21084)

* fix activation_functions deps, test=develop, test=document_fix

* add error_codes_proto deps, test=develop, test=document_fix

* try delete enforce.h, test=develop, test=document_fix

* change cuda enforce & add example (#21142)
test=release/1.6

* Add asymetric padding support for mkldnn pooling
test=develop

* Add asymetric padding support for mkldnn conv
test=develop

* Add asymetric padding support for mkldnn conv_transpose
test=develop

* add support to gcc8, add docker env
* remove the warning issue

test=develop

* test=develop, communicator_is_sgd_optimizer flags

test=release/1.6

* - 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

cpu机器在gpu库上运行paddle出core，原因是由于缺失显卡driver，显卡driver与cuda driver不匹配

加上driver check解决该问题

* How to write custom op needs to follow framework OP spec.
* Package fluid_framework.so and headers into whl.
* Add paddle.sysconfig.get_include() and paddle.sysconfig.get_lib() to get include dir and lib dir.
* Export some C-APIs to merge OpInfo between core.so and custom_op.so.
* Add unit testing.
* Update API.spec.

* fix pool2d pool3d:
1. support asymmetric padding;
2. support padding algorithm:"SAME" and "VALID";
3. support channel_last: data_format NHWC and NDHWC;
4. support inferring shape when input with negative dims in compile time;
5. change doc of python API and c++;
6. fix bug in cuda kernel when Attr(adaptive) is true.

test=develop,test=document_preview

* fix 'tensors' to 'Tensors'. test=develop,test=document_preview

* add test for converage ValueError.test=develop,test=document_preview

* resolve conflict in test_pool2d. test=develop

* shape and optimize paddle error message stack, test=develop

* limit exception type & add unittest, test=develop

* fix multi-platform problem, test=develop

* fix related unnitest failed, test=develop

* add doc & fix unittest errors, test=develop

* fix function name error, test=develop

* update tensor test exception msg compare, test=develop

* remove unittest on win32, the dir format is different, test=develop

* remove useless package, test=develop

* add paddle enforce handler unittest, test=develop

* add exception checkout, test=develop

* fix coverage failed, test=develop

* fix op registry test failed, test=develop

* refactor whole pr, test=develop

* remove test in CMakelist, test=develop

* fix coverage, test=develop

* Fix conv2d+dequantize squash for residual fusion

test=develop

* Correct int8 input

test=develop

* Add if exclude or include padding in pool2d mkldnn

test=develop

- First implementation of BWD and FWD of pooling mkl-dnn

- Compilation fix

- Fix

- Fix

 - Fix

- Fix to crash

- Compilation fix

- Combined AcquireBacward with Fwd

test=develop

* Add RecordHistoryLocalExecScopes
test=develop

* refine reallocate of workspace size, test=develop

* add lock to cudnn handle calls, test=develop

- LRN mkl-dnn kernel refactor

test=develop

- compilation fix

- Another compilation fix

- Compilation fix

- another compilation fix

- compilation fix

- Crash fix

- optional LRN mkldnn workspace

- Added mid allocation

- Workaround for tests

- Removed gradient from is_test ut

- Removed mid for inference

- Reverted LRN mid removal for is_test

- PADDLE_ENFORCE adjusted

- Rebase to templatization commit

- Compilation fix

- compilation fix

test=develop

- lint

test=develop

- Fix to crash

- Rebase to recent codebase

 - lin

- lint

- compilation fix

* fix conflicts
test=develop

* change mask_bias_reorder
test=develop

* add ComputeMask function to make code clear
test=develop

* change according to reviews
test=develop

* change according to reviews
test=develop

* Add template functions for Acquire primitive/primitive_desc
test=develop

* Move acquire primitive descriptor to protected section
test=develop

test=develop

test=develop

test=develop

test=develop

- fix to BWD

test=develop

TemporaryAllocator is a singleton used for allocating memory for Cudnn. Since it is a singleton, we can delete it for better performance in memory.

We replace TemporaryAllocator by CUDADeviceContextAllocator and CUDADeviceContextAllocation, which uses stream callback to delete the memory allocated for the stream to avoid singleton.

Also added data_feed_proto to operator to fix CI in CPU compilation

* MKLDNN handler cleanup

* MKLDNN handler cleanup
test=develop

Add document annotations for FLAGS that need to be open to external developers test=develop (#19692)

Add document annotations for FLAGS that need to be open to external developers

* paddle::framework::vectorize() templatization

test=develop

* update pybind/imperative.cc

test=develop

* revert update on unsqueeze_op.cc and warpctc_cudnn_op.cu.cc

test=develop

* Add the dynamic load of nvrtc, and support runtime compiling of CUDA kernel using nvrtc.
test=develop

* Call CUDA driver api to launch the kernel compiled by nvrtc.
test=develop

* Disable for mac and windows.
test=develop

* Refine the codes to support manually specified num_threads and workload_per_thread.
test=develop

* Refine the CUDA kernel to support large dims.
test=develop