* support generating code of opmaker for backward op invoke forward op

* gsupport code-gen of opmaker for sparse op

* refind logic of choose phi kernrel

* fix complie budg

* fix code_gen bug

* fix bug

* fix kernel signature code-gen

* fix complie bug of VarType

* fix complie bug of VarType

* fix test_sparse_conv_op

* fix test_sparse_norm_op

* Fix bug of reduce_sum op. When input.numel() > INT32_MAX, its result
is wrong.

* support pure bfloat16

* support bf16 linear

* update PR to pass CI

* tiny fix where_grad_kernel.cu

* Support bfloat16 type for reducer and sharding.

* Fix some bug.

* Polish code.

* Polise code.

* Add bfloat16 datatype in fill_grad kernels.
Co-authored-by: Nsneaxiy <sneaxiy@126.com>

* namespace modify

* update by comment

* add sparse reshape

* change the dtype in all test cases to int64

* just one test case

* modify comments

* Update test_sparse_reshape_op.py

* chang the type of "shape"  from  vector<int64_t>  to  IntArray

* check whether sp_out.to_dense() is the cause  of error

* print sp_out

* Update reshape_kernel.cc

* use numpy to generate the equal paddle tensor

* just check dense_tensor.numpy()

* check cpu and cuda versions

* Update test_sparse_reshape_op.py

* supply all test cases for cpu forward coo kernel

* test forward coo cuda kernel

* change configuration of cuda kernel

* keep only one test case

* test coo cpu kernel (forward and backward)

* row major or column major ???

* test cuda coo forward kernel

* complete declaration and registration

* Update __init__.py

* rebuild

* retrigger CI

* add cudaMalloc and cudaMemcpy  in  ReshapeCooKernel  and change back to row major order in a cuda dense tensor

* midify minor error

* test only cpu coo forward kernel

* add all test cases for coo forward kernel  (both cpu and gpu)

* test all forward kernels (coo, csr; cpu, gpu)

* add all test cases for all kinds of kernels

* just retrigger CI

* Update sparse_ops.yaml

* Update sparse_ops.yaml

* Update sparse_ops.yaml

* resolve conflicts

* Update sparse_ops.yaml

* don't specify tensor place

* new shape has -1 or 0 in it

* Update unary_grad_kernel.h

* correct lvalue error

* code style

* Update sparse_backward.yaml

* Update sparse_ops.yaml

* Update unary_kernel.h

* Update unary.py

* Update sparse_backward.yaml

* Update unary.py

* code style

* code style

* code style

* Update unary.py

* specify tensor place explicitly

* do not use numpy array

* use numpy array in unit test again

* modify example code in docstring

test=kunlun

* add singleton to custom device

* Update custom_device.cc

Init device_init_flag_ in default

* draft with debug print

* refind logic of choose phi kernrel

* fix complie budg

* Revert "【Hackathon No.56&38】deformable_conv_v1 算子实现 float16 数据类型支持&前向运行加速 (#46111)"

* Correct the logic and remove unnecessary template param

* fix error throw

* fix print format

* fix ci

* remove PADDLE_WITH_MKLDNN, test white_list=abs

* fix unique_ptr

* fix op.Type()

* remove TODO in kernel_dispatch.h

* remove IndicateVarDataType function, update white_list

* remove mkldnn hard code

* add comments

* fix ==

* update mkldnn_op_list

* delete hard code of OPs

* update mkldnn_op_list

* update mkldnn_op_list, remove interp

* add error check for ExecutionContext

* update mkldnn_op_list, remove transpose2_grad

* remove interpolate mkldnn

* remove fill_constant mkldnn

* opt HasAttr in DygraphExecutionContext

* deprecated commit, test mkldnn_white_list

* deprecated commit, test mkldnn_white_list

* deprecated commit, test mkldnn_black_list

* update mkldnn_op_list, add assert error op

* solve cudnn related op

* fix error

* add mkldnn fallback in phi_utils.cc

* remove mkldnn fallback in phi_utils.cc

* opt code implementation

* polish Copyright License

This reverts commit 8a5f17e8.

* fix some ops for int64 range

* update error message

* [Zero-Dim] support input 0D Tensor for unary api

* fix CI

* remove using lodtensor part1

* polish history code format

* add fp16 data type for set_value

* cancel flip modification

* add fp16 dtype support for set_value

* add yaml entry for rnn and rrnn_grad, move infershape function for rnn_grad to phi infer meta

* WIP: move rnn kernrl to phi

* Change the code generation to avoid converting from intializer list to tuple of heterogeneous types.
This is only triggered when an api has intermediate outputs, and the result of the outputs are of heterogeneous types.

* fix the bug that when none in a vector of tensors requires gradient, the conversion to InferShapeContext to InferMetaContext (a.k.a. BuildInferMetaContext) produces errorous results.

* fix ci bugs

* fix ci bugs

* fix ci bugs

* modify code according comment
Co-authored-by: Nchenfeiyu <chenfeiyu@baidu.com>

* op migrated, Copy(OneDNNContext, ...) added

* mutable_data & op registration in fluid removed

* refactoring

* OneDNNGetDataType to uppercase

* missing cpu check added, handler moved to .h file

* name changed to transpose_grad

* Copy changed back to TensorCopy

* Resizing corrected, Copy(OneDNNContext) removed

support fp16 for deformable conv

* enable hard_swish_grad unit test

* remove unused argument

* - some more MD changes

* - lint

* - compilation fixes

* - compilation fixes

* - lint

* - fix

* Fix undefined reference PD_IntArrayGetElementCount

* Delete PD_IntArrayGetSize Unused