* 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

* sparse infer_meta

* rename the member function of SparseTensor

* use shorter function names

resort .cu headers, set clang-format not sort include block and consider .cu as main source file (#43633)

* fix to_sparse_csr

* use GpuMemcpy and GpuMemset

* sparse convert kernel support double dispatch by indices dtype

* cudaMemcpyKind->gpuMemcpyKind

* remove storage

* add glog include

* add glog include

* add glog include

* remove shared_storage

* fix bug

* fix rnn bug

* move the common function to kernel/funcs/sparse/

* add namespace

* rm unused file

* move func

* reuse code

* fix incorrect dims settings

* sparse conv3d

* fix out dims

* test performance

* test large shape success

* opt scatter, double performance

* test float16

* remove profiling code

* remove pten

* opt code lines

* correct boundary judgment

* only cpu

* test ci

* test ci

* remove the including paddle/fluid header; extract the conmmon function

* opt code lines

* use DenseTensor::data() instead of mutable_data

* return rulebook for backward

* specify layout

* rename:conv -> sparse_conv3d

* change Vector to std::vector and provide MixVector class as a helper wrapper class

* solve the multi-gpu hang problem

* remove the duplicate template instantialize

* Copy vector to cpu

* add CopyToCPU

* xxx

* final version: fix the problem of all reduce

* remove mixvector dependence

* fix

* merge

* fix code

* fix by CI

* unify register macro

* rename declare macro

* fix infrt error

* 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

* fix code conflict

* clear cache

* just try

* adjust the Empyt dev_api

* fix merge conflict

* fix sparse_utils_kernel

* implement AllocateFrom

* dense_to_sparse_coo

* optimize unit testing; support rocm

* 1. delete fluid related header file
2. update the copyright

* fix hipMemcpy

* update dense_to_sparsecoo

* add namespace sparse

* sparse_csr_to_dense

* test to_sparse_coo: csr_to_coo

* fix writing error

* to_sparse_csr: dense_to_sparse_csr and sparse_coo_to_csr

* fix check shape

* fix unit test

* to_dense: sparse_coo_to_dense, sparse_csr_to_dense

* replace CUDADeviceContext by GPUContext

* implement AllocateFrom

* dense_to_sparse_coo

* optimize unit testing; support rocm

* 1. delete fluid related header file
2. update the copyright

* fix hipMemcpy

* update dense_to_sparsecoo

* add namespace sparse

* sparse_csr_to_dense

* test to_sparse_coo: csr_to_coo

* fix writing error

* to_sparse_csr: dense_to_sparse_csr and sparse_coo_to_csr

* fix check shape

* fix unit test

* replace CUDADeviceContext by GPUContext

* dense_to_sparse_coo

* optimize unit testing; support rocm

* 1. delete fluid related header file
2. update the copyright

* fix hipMemcpy

* update dense_to_sparsecoo

* add namespace sparse

* sparse_csr_to_dense

* test to_sparse_coo: csr_to_coo

* fix writing error

* dense_to_sparse_coo

* optimize unit testing; support rocm

* 1. delete fluid related header file
2. update the copyright

* fix hipMemcpy

* update dense_to_sparsecoo

* add namespace sparse