* 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

* draft with debug print

* 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

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

* 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

* Optimize performance of depthwise_conv_bwd of filter

* op-benchmark

* fix

* op benchmark

* merge bwd

* Optimize performance of depthwise_conv_bwd

* fix

* migrate sigmoid with cross entropy, and tile xpu kernels to phi, test=kunlun

* migrate add_n kernep to phi, test=kunlun

* fix bugs of tipc, test=kunlun

* support pure bfloat16

* support bf16 linear

* update PR to pass CI

* tiny fix where_grad_kernel.cu

* add bfloat16 to selu_grad to pass CI

* fix selu grad compilation error

* Move valid check from python to kernel

* fix error throw

* fix

* invalid label check

* fix

* Revert "fix"

This reverts commit 79fad6799cfa4b30423dbc84e67d7d843d22b84a.

* Revert "invalid label check"

This reverts commit 402a9707390ad5386b3222e85844b92d2e9b9fa4.

* Revert "fix"

This reverts commit 09ba3080ee0587447f875c19cdf060485f15ae3b.

* Revert "fix error throw"

This reverts commit a901bfcc2179d5c120ec29af766f392b122dab52.

* Revert "Move valid check from python to kernel"

This reverts commit baa03cc4ef82d8d45516c30dfb52bf5aead30748.

* final fix

* fix

* fix

Add index_select, index_select_grad, reduce_min kernel and their unittests for kunlun. Add registers of index_select, index_select_grad, reduce_min, sqrt, sqrt_grad to xpu2_op_list.test=kunlun. (#46557)

* fix P40 topk: Make the optimized topk compatible with P40.

* fix P40 topk: Make the optimized topk compatible with P40.

* fix P40 topk: Make the optimized topk compatible with P40.