* Fix TensorRT detection bug

1. Add new search path for TensorRT at tensorrt.cmake
2. Add better debug message
3. Fix the bug of detection of TensorRT version

In NVIDIA official docker image, TensorRT headers are located at
`/usr/include/x86_64-linux-gnu` and TensorRT libraries are located
at `/usr/lib/x86_64-linux-gnu`, so using `-DTENSORRT_ROOT` will
fail to detect TensorRT.

There is no debug/warning message to tell developer that TensorRT
is failed to be detected.

In later version of TensorRT (e.g. v6), `NV_TENSORRT_MAJOR` is
defined at `NvInferVersion.h` instead of `NvInfer.h`, so add
compatibility fix.

* Fix TensorRT variables in CMake

1. Replace `${TENSORRT_ROOT}/include` with `${TENSORRT_INCLUDE_DIR}`
2. Replace `${TENSORRT_ROOT}/lib` with `${TENSORRT_LIBRARY}`

Manually type path may locate incorrect path of TensorRT. Use the
paths detected by system instead.

* Fix TensorRT library path

1. Add new variable - `${TENSORRT_LIBRARY_DIR}`
2. Fix TensorRT library path

inference_lib.cmake and setup.py.in need the path of TensorRT library
instead of the file of TensorRT library, so add new variable to fix it.

* Add more general search rule for TensoRT

Let system detect architecture instead of manually assign it, so
replace `x86_64-linux-gnu` with `${CMAKE_LIBRARY_ARCHITECTURE}`.

* Add more general search rule for TensorRT

Remove duplicate search rules for TensorRT libraries. Use
`${TENSORRT_LIBRARY_DIR}` to get full path of libnvinfer.so

test=release/1.6

* ADD NV JETSON SUPPORT
test=release/1.6

* CHERRY_PICK: specify the auto growth allocator for inference.
test=release/1.6

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

add executor.FetchHandler for train/infer from the dataset

test=release/1.6

* Add multihead op for ernie opt

* Refine softmax

* Refine kernel.

* Refine cuda kernel

* Refine cuda version

* Refine cmake

1.support asymmetric padding;
2.support padding algorithm:"SAME" and "VALID";
3.support channel_last: data_format NHWC and NDHWC;
4.change doc of python API and c++;

test=release/1.6

* update operator compatible info, test=develop

* revert cmake/version.cmake, test=develop

* add unit_tests and fix bugs, test=develop

* update ../paddle/fluid/framework/framework.proto, test=develop

* fix bug of paddle/fluid/inference/api/analysis_predictor.cc, test=develop

* update paddle/fluid/framework/version_test.cc, test=develop

* add comments and rename interfaces, test=develop

* add dgc.tgz to bos

* Add fc_elementwise_layernorm_fuse pass and unittest.

* Add fused_fc_elementwise_layernorm op and its GPU kernel.
test=develop

* Apply fc_elementwise_layernorm_fuse_pass to GPU inference.

* Add the setting of attrs in the definition of binary_op.
test=develop

* Add comment.

* Implement the unittest.
test=develop

* Change the unittest name of layer_norm.
test=develop

* add deformable conv v1 op, 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

* Refine the codes related to fc op.

* Add GPU implementation for fc functor.

* Apply fc_fuse_pass in GPU inference.
test=develop

* Change the cmake for fc op.

* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.

* Add an attribute to set the activation type in fc_op.

* Enhance the unittest of fc_op.
test=develop

* Remove the declaration of FCOpGrad back to the header file.
test=develop

* Set default value for newly added arguments in test_fc_op.
test=develop

* remove -Wmaybe-uninitialized warning

test=develop

* remove uninitialized op_handle_ in scale_loss_grad_op_handle.cc

test=develop

test=develop

* test=develop, Support for online compilation of openblas

* test=develop, Modify the prefix of openblas static library

* Support looking up embeddings from BoxPS.
* Add a _pull_box_sparse op, for now this op is not exposed to users.
* Add a BoxHelper class, providing 'BeginPass', 'EndPass', 'FeedPass' functions and so on.
* Add 'BoxPSDataset' in python code.
* Add a compile options WITH_BOX_PS and a MACRO PADDLE_WITH_BOX_PS.
* Add UT.
* More concrete information pls refer to: https://github.com/PaddlePaddle/Paddle/pull/18982

* Implement the operator with sprase matrix multiply

* Update the URL of mklml library.

test=develop

* Disable MKLML implematation when using no-linux.

test=develop

* Ignore the deprecated status for windows

test=develop

* fix compilation issue in windows vs2017, test=develop

* fix gtest lib not found issue, test=develop

* test=develop,fix the inference library compilation bug on windows

* test=develop,Fix the inference library compilation bug on windows

* test=develop,fix the bug that PYTHON_EXECUTABLE not exists

* test=develop,fix the inference library compilation bug on windows

test=develop

* add tensorrt support for windows

* Add support for dynamic code analysis (Sanitizers)
test=develop

* Move options to one option

test=develop

* Missing check

test=develop

* upgrade ngraph to v0.24 test=develop

* simplify io test=develop

test=develop

test=develop

test=develop

test=develop