* move "paddle/phi/backends/gpu/gpu_device_function.h" to phi

* update copyright years

* rm "fluid/platform/device/gpu/gpu_device_function.h" in phi

* fix rocm-complie bugs

* add elementwise_div

* refine rocm

* refine code

* refine op register

* solve conflict

* refine unittest

* refine unittest precision

* add rocm

* rename pten dir to phi

* rename namespace to phi

* rename infrt pten dir to phi

* resolve conflict

* rename pten to phi in cmake

* revert all infrt change

* change needed files

* fix infrt failed

* fix inference failed

* pten matmul cuda kernel support bf16

* fix pten kernel name

* add matmul_grad bf16 kernel

* add emptylike bf16 kernel

* fix compile

* suppport rocm

* fix error

* fix rocm

* add bf16 header file

* fix compile

* first commit

* fix wrong filename

* fix the wrong spell name

* fix gpu config warper

* modify according to pr advices

* fix GpuLauchConfig1D api bugs

* change the config for dropout grad

* fix bugs

* modification according to pr advices

* modification according to pr advices

* refine structure for cuda and rocm

* update

* update

* update

* update

* 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 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

* 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

* Refine the beam_search op and test.

* A basic CUDA implementation of beam_search for small batch_size.

* Implement CUDA kernel for beam_search_op.

* Use multiple CUDA threads in the same block to select the top beam.

* Update the python api of beam_search op.

* Enable extend function in CPU kernel of beam_search op.

* Unify the CUDA codes.
test=develop

* Unify the CPU kernel of beam_search op.

* Ensure the seletced items of beam_search_op's CPU kernel sorted by scores.

* Update the description of beam_search in API.spec.

* Enable the use of CUDA kernel in beam_search op.

* Exclude the beam_search's CUDA unittest when there is no CUDA gpu, and delete some debuging statements.
test=develop

* Follow comments.
test=develop

* Call the CPU kernel for beam_search op when batch_size > 4.
test=develop

* Remove the except of is_empty op in PrepareData.
test=develop

* "fix bug"

* "add test case"

* cherry picked

* "cherry picked platform"

* "add comment"

* "fix ci"

* fix __shfl_down_sync_ of cross_entropy

* use reduceSum

* "fix ci"