* Generate code coverage reports only for incremental files, test=develop

* Generate code coverage reports only for incremental files, test=develop

* Generate code coverage reports only for incremental files, test=develop

* test for diff python file, test=develop

* fix no python diff report, test=develop

* add cc test file, test=develop

* fix bug in generic.cmake, test=develop

* for debug no cc report, test=develp

* modify compire branch form test_pr to test, test=develop

* fix bug, test=develop

* test for h file changed, test=develop

* debug for redefinition of argument optimize error, test=develop

* close -o3 for test, test=develop

* remove -o3 for test, test=develop

* remove coverage option for nvcc, test=develop

* use CMAKE_CXX_FLAGS open coverage option when header file changed, test=develop

* reopen -o3, test=develop

* remove debug code, test=develop

* remove unused code, test=develop

* fix 2.0 api, test=develop

* fix api, test=develop

* add ReduceLROnPlateau

test_mnist failed on CUDA11. We found that it is due to PaddleInference IR Optimization after debugging. We disable it in this PR and we will re-enable it after PaddleInference fixes it.

[Dy2Stat] Fix bug: the return statement should be transformed to an equivalent Paddle/Python if statement, which depends on if conditions of the return stmt. (#29165)

GridGenerator model failed because the output shape of `linspace` is (-1). The reason is that C++ InferShape fixes the shape to (-1): 

https://github.com/PaddlePaddle/Paddle/blob/5da3d514ebaa6fffd48c4a2e6bb5b16268dae92e/paddle/fluid/operators/linspace_op.cc#L49

We cannot set the shape in C++ infer shape because this Tensor may not be initialized during compile time, but when input `num` of `linspace` is an integer, we know the shape at compiler time. This PR simply set the shape in Python and add GridGenerator as unittest.
 

* add reducer

* refine envent for memorycopy

* add concat&split for allreduce

* apply concat & split for fuse tensor

* fix nccl dep

* fix the untest, compile problem and ddp initialize problem

* fix untest for mac & add some comments & solve the repeated param in sublayers

* fix untest for windows & fix document

update expand as op to use the shape of the target tensor instead of the target tensor itself. (#29020)

* update, test=develop

* alias yolo_loss & decode_yolo_box to paddle.vision. test=develop

add paddle.subtract, optimize paddle.maximum and paddle.minimum 

* fix doc example, test=develop, test=document_fix

* solve pretty table dependent in flops api

* add unittest dependent

* temp

* fix Categorical en doc

* fix doc for apis

* remove numpy in sample code

* enhance logger callback for benchmark

Add eigen gru and fix the dropout bug in the rnn 

[Dynamic-to-Static] Support **kwargs as input of the function which is decorated by `jit.save.to_static` (#29098)

* Optimiz the unittest test_imperative_out_scale

test=develop

* remove -DSUPPORTS_CUDA_FP16 in cuda.cmake

* comile with cuda9

* add some unittest

* notest;test=coverage

* add unittest for trt plugin swish && split

* update ernie unittest

* fix some error message

* remove repeated judgement of CUDA version in mbEltwiseLayerNormOpConverter

* fix comile errror when CUDA_ARCH_NAME < Pascal"

* fix comile error

* update unittest timeout

* compile with cuda9

* update error msg

* fix code style

* add some comments

* add define IF_CUDA_ARCH_SUPPORT_FP16

* rename IF_CUDA_ARCH_SUPPORT_FP16 to CUDA_ARCH_FP16_SUPPORTED

* add symlink force for unittest

* open unittest

* fix interpolate example, test=develop;test=document_fix

* fix format, test=develop, test=document_fix

* update upsample doc, test=develop, test=document_fix

* 1. grid_sample
1.1 fix has_print
2. conv1d_transpose
2.1 fix code_example error
3. conv1d
4. affine_grid
4.1 has_print
4.2 has_disable_static
5. Conv1DTranspose
5.1 fix code_example error
5.2 has_disable_static
6. Conv1d
6.1 code_example
6.2 has_disable_static

* update, test=develop

Fix ops doc for some ops 

* split train_mode and has_grad

* fix format

* fix ci problems

* fix sample code

* add Inmemorydataset