* 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