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

* Enhance the function of fused_elementwise_activation_op

* enhance unit test

* Clean Code And Add Doc

* Add compound functors

* Fix doc and enhance unit test

* define Dx and Dy for d_binary_func

* add mul_scale

* add mul_scale

* add elementwise_mul

* code refine

* code refine

* add doc

* add  AsIntermediate

This reverts commit bf3c3496.

* "cherry picked operators changes"

* "remove duplicated code"

* "add constant setter"

* "add get expected kernel"

* "fix ci"

* "add fill constant"

* "add gradient register"

* "make some enhance"

* "better format"

* "fix typo"

* "fix reuse"

* "fix get expected kernel"

* "change the mkldnn code"

* "fix mkldnn"

* "fix mkldnn failed test"

* "add comment"

* fix __shfl_down_sync_ of cross_entropy

* use reduceSum

* "fix ci"

* "re-commit "

* "picked up"

* "fix ci"

* "fix pdb hang up issue in cuda 9"

* add cuda_device_functions.h

* move reduceSum to elementwise_op_function.h

When the second argument contains batch dimension, the axis should be 0.

Also makes elementwise ops more tolerant at handling tensors with trailing
singular dimensions.