Implement FunctionTraits to support two kinds of elementwise functor and remove some old codes for broadcast. (#35487)

* enhance error message when x or y is empty in elementwise_op

* format code

* format code

* [ROCM] fix test_gru_rnn_op

* [ROCM] fix test_expand_op

* [ROCM] fix test_cross_entropy_loss

* [ROCM] fix test_conv_nn_grad

* [ROCM] fix test_bilinear_tensor_product_op

* [ROCM] fix elementwise_op_function

* [ROCM] fix test_lstm_cudnn_op

* [ROCM] fix test_gpu_package_without_gpu_device

* [ROCM] fix test_gru_unit_op

* [ROCM] fix test_imperative_optimizer

* [ROCM] fix rnn

* [ROCM] fix group_norm_op

* [ROCM] fix test_pool3d_api

* [ROCM] fix test_pool3d_op

* [ROCM] update fluid elementwise op for rocm (part10), test=develop

* update, test=develop

* address review comments, test=develop

fix the broadcast for the large second input 

reduce the  occupied size  of memory for the fused pattern of elementwise_add Op and activation Op(relu Op for example) (#29885)

test=develop

* Remove the error in the elementwise op, use the backup mode to calculate

* 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

Those ops add the kernel message enhancement, as follows
paddle.fluid.layers.elementwise_add	
paddle.fluid.layers.elementwise_div
paddle.fluid.layers.elementwise_floordiv
paddle.fluid.layers.elementwise_max	
paddle.fluid.layers.elementwise_min	
paddle.fluid.layers.elementwise_mod	
paddle.fluid.layers.elementwise_mul	
paddle.fluid.layers.elementwise_pow	
paddle.fluid.layers.elementwise_sub

elementwise function used before definition then failed in cuda 8, move it ahead.

* improve elementwise performance.

* Add contiguous check, test=develop

* Improve elementwise performance.

Elementwise performace is poor as walk into CommonGradBroadcastCUDA, add some new kernels for different data pattern.

* Add some cuda kernel to speedup common broadcast cases. test=develop

* Add more test cases and fix cuda kernel bug. test=develop

* Remove tests as cpu percision fails.test=develop

* Refine SplitDims, test=develop

* Change file mode, test=develop

elementwise broadcast function enhancement

For small case use 1D block is better than 2D block.

Refer to this issue: #19275

test=develop

* double backward, elementwise_div

* fix dx empty. test=develop

* bug fix (#17392)

fix secure bug

* Eanble stack operator for a Ngraph, test=develop (#17406)

* fix sqrt_grad_grad unittest. test=develop (#17410)

* fix sqrt_grad_grad unittest. test=develop

* disable sqrt_grad_grad unittest. test=develop

* test=develop, fix unittest

* test=develop, fix unittest

* test=develop, fix unittest

* test=develop, fix bug

* fix unittest. test=develop

* fix unittest dx. test=develop

* tmp fix! for test... test=develop

* reduce tmp, test=develop

* test=develop, reduce tmp

* fix broadcast unittest. test=develop

* fix format. test=develop

* refine code. test=develop

* refine code. test=develop

* refine GetDoubleGradSafeTensor. test=develop

* fix format. test=develop

* add double grad for elementwise_mul. test=develop

* remove comment. test=develop

* fix grad sum. test=develop

* fix for axis expand. test=develop

* add test for axis expand. test=develop

* Refine elementwise kernel.

Add a simple cuda kernel if grad x and y both exist
Use 2D block cuda kernel to do broadcast.

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* refine code.

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* refine code.

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

test=develop

* wip simplify operator framework

* wip

* wip

* done test=develop

* clean test=develop

* fix test=develop

* fix deps test=develop

* fix cpu build test=develop

* fix tensorrt build test=develop

* fix tests test=develop

* fix test=develop

* fix cpu build test=develop

test=develop

* add fp16 backward support
test=develop

* add sum_op fp16 test

* disable test_dist_save_load
test=develop

* add check_grad for sum

* add unit test for softmax_grad fp16
test=develop

* add scale_op unit test

* add mul_grad_op unit test for fp16

* add cross_entropy_grad and eman_grad unit test for fp16
test=develop

* fix cross_entropy unit test

* add pool2d fp16 unit test

* refine conv2d fp16 unit test
test=develop

* refine activation unit test
test=develop

* fix ci
test=develop

* follow zhihong's comment, copy from https://github.com/PaddlePaddle/Paddle/pull/12796
test=develop

* Add Preface

* Add demo code

* Save file

* Refine code

* seems can work

* use elementwise strategy

* Use ElementwiseComputeEx

* Add comments

* extract functions from operator

* Refine code

* Follow comment

* code refine

* add op_fuse  pass

* add backward

* code refine

* use TopologySortOperations

* follow comments

* refine IsFusible

* code enhance

* fix op_fusion_pass

* refine code

* refine fuse_elemwise_act_op

* adjust the input and output

* refine logic

* add intermediate_edge

* disable inplace

* follow comments

* refine logic

* follow comments

* Remove the removable IntermediateOut

* change strategy

* code refine

* enable fuse backward

* code refine

* code refine

* rename unit test

* follow comments