* support generating static code of high order grad op by yaml

* polish code

* standard_api

* add hardtanh

* gene static graph code for ceil, expm1 op

* gene static graph code for some activation op

* fix bug

* revert doc of silu and logsigmoid

* add extra attr property set

* add type_info for all context

* add onednn context to all context

* fix context compile error

* simplify conv kernel args

* pass runtime attr into dev_ctx

* fix marco error

* clear conv_grad_kernel extra args

* merge conv_grad_grad into conv_grad

* clear conv2d_grad_grad extra attrs

* clear yaml and eager extra attr

* fix conv1d error

* change to thread local

* fix npu compile failed

* try to fix windows compile failed

* add conv2d onednn phi kernel

* fix ci bugs (#36)

* fix compile bugs (#38)

* fix extra input transform bug (#39)

* support dynamic created attr (#40)

* reset extra info gen code

* rm conv_grad_grad kernel

* reimpl pass attr adapting

* add int attr support

* remove vector inputnames creating

* fix map at error

* Update paddle/phi/kernels/onednn/conv_grad_kernel.cc
Co-authored-by: NSławomir Siwek <slawomir.siwek@intel.com>

* remove useless extra attrs

* replace mkldnn_engine by onednn_engine
Co-authored-by: NYuanRisheng <yuanrisheng@baidu.com>
Co-authored-by: NSławomir Siwek <slawomir.siwek@intel.com>

* standard api

* fix ci bugs

* fix ci bugs

* fix ce bugs

* generate static graph code for some activation op

* fix example code of cosh

* fix inference perfermence problem caused by selecting cudnn kernel for softmax

* recover use_cudnn in opmaker of softmax

* gene static graph code for exp

* refactor the doc of exp

* fix bug

* fix bug

* update doc of exp

* fix sparse op

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

Fix the bug where the device memory address appears in abs_grad kernel fallback to CPU. test=kunlun (#47186)

* rename op in yaml

* fix test_layout_autotune

* fix layout autotune of transpose

* 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

* 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

* 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

* remove using lodtensor part1

* polish history code format

* 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>

* select highest priority layout

* opt performance, save virtual table find

* add datatype check for ParseKernelKeyByInputArgs

* polish error message

* Actually, einsum has vector<Tensor> inpute with DataType::COMPLEX64, see test_einsum_v2.py

* headerfile remove enforce.h

* remove needless using tensor

* remove needless using tensor

* resolve conflict

* replace tensor using

* fix format error

* revert needless changing

* fix rocm and npu compile error

* fix cinn compile error

* fix format error

* fix mkldnn format error

* fix mkldnn format error

* fix cinn compile error

* fix cinn compile error

* fix cinn compile error

* resolve conflict

* change BackendSet from 64bits to 32bits

* fix _MSC_VER error, __lzcnt32->__lzcnt

* fix __GNUC__ error, __builtin_clzl->__builtin_clz

* fix clip_extra code in remove_training_info

* revert rnn opmaker clear

* enable eager mode on xpu, test=kunlun

* add numpy support to xpu

* fix tensor using error

* fix  error, test=kunlun

* fix failed tests, test=kunlun