* modify complex template for elementwise ops

* modify mul, div grad struct

* add complex template for CudaShuffleDownSync CudaShuffleXorSync funcs and fix the bug when delete cuda<9000

* fix shuffle func args bug

* fix shuffle func args bug

* fix shuffle func args bug

* add conj op for complex types

* add conj for complex types

* add more test case

* add conj_op test

* modify conj api and impl

* add complex type for fill_constant_op xpu

* add setConstant for complex type

* remove complex conj test file

* user define grad for test_conj_op

* add test case for static mode of conj api

* modify conj doc

* change input args name to x

* remove useless codes

* conj support real types

* add conj test case for real number

* delete no need to calculate inputs in dygraph op_test

* delete no need to calculate inputs in dygraph op_test

* modify grad of mul for complex types

* fix the grads of inputs args order not match bug

* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types

* add test cases for complex elementwise, matmul and getitem unittest

* add test cases for complex types

* add test cases for complex matmul unittest

Improve elementwise operators performance in same dimensions

* update elementwise double grad to save gpu memory, test=develop

* update elementwise_mul/div_grad_grad to save memory, test=develop

* remove eval function in eigen statement to save memory, test=develop

* add unittest for elementwise_div_grad_grad without dout, test=develop

* add unittest for elementwise_add_grad_grad without ddx, test=develop

* add float16 cuda kernel for elementwise double grad op, test=develop

* Optimize the elementwise op with CUDA kernels.
test=develop

* Support setting of attr in op config file.
test=develop

* Add the support the setting dtype and initializer in config.
test=develop

* Save workspace.

* Add initializer "zeros".
test=develop

* Fix compiling error.

* Support the use of existed file to initailize tensor in op_tester.

* Use eigen to optimize the elementwise_add/mul for the case that x and y have the same dims.
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>

* wip

* wip

* wip

* wip for test

* add fp16 tests test=develop

* fix cpu build test=develop

* fix test=develop

* fix py3 tests test=develop

* fix lr_scheduler dtype test=develop

* fix test=dvelop

* test fix ci compile test=develop

* fix build and merge test=develop

* fallback momentumop change to general test=develop

* make fp16 lr schedule simple test=develop

* fix ut test=develop

* fix tests test=develop

* remove fp16 learning rate cast test=develop

This reverts commit 3d750f9c.

* wip

* wip

* wip

* wip for test

* add fp16 tests test=develop

* fix cpu build test=develop

* fix test=develop

* fix py3 tests test=develop

* fix lr_scheduler dtype test=develop

* fix test=dvelop

* test fix ci compile test=develop

* fix build and merge test=develop

* fallback momentumop change to general test=develop

The macro should be defined by compiler rather than by source.

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

This reverts commit bf3c3496.

* "cherry picked operators changes"

* "remove duplicated code"

* "add constant setter"

* "add get expected kernel"

* "fix ci"

* "add fill constant"

There are mainly following fixes:

- take `DeviceContext` as the template parameter of math functors and OpKernel instead of `Place`
- remove `eigen_device` interface in base class  `DeviceContext`
- remove `GetEigenDevice` interface in `ExecutionContext` and base class `DeviceContext`
- remove unused `platform::EigenDeviceConverter`
- rename `REGISTER_OP_GPU_KERNEL` to `REGISTER_OP_CUDA_KERNEL`
- rename `USE_GPU_ONLY_OP` to `USE_CUDA_ONLY_OP`

Elementwise operator add/sub/mul/div

Add element-wise multiplication operator

Make implement an operator less noisy.

* Implement InferShape and register them, give a stub Kernel method
  by LOG(INFO)