fix uninitialized, tautological-constant-out-of-range-compare and literal-conversion warning on macos (#47341)

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

* recover use_cudnn in opmaker of softmax

* return proper state

* fix for dims

* fix

* support selected_rows kernel for multiply in dygraph

* delete useless code of slice in fluid

* fix complie bug

* move slice_array from fluid to phi

* fix strided_slice_op_npu

* 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)

* fix indices

* Add infer prune function

* Update phi.cmake

* Update operators.cmake

* add fusion op

* rename op in yaml

* fix test_layout_autotune

* fix layout autotune of transpose

Enable to record whether the conv algo is got by exhaustive search to fix autotune cache bug. (#47065)

* [Dy2Static] Remove GradTransformer
1. fix einsum infershape bugs.
2. remove grad_transformer and unify paddle.grad and paddle.static.gradient.
3. add dygraph_and_dy2static_only decorator for dy2static.

* fix bugs

* rename

* add embedding range check

* change head file

* change head file

* fix

* [XPU] update xpu cmake to 1016. test=kunlun

* fix special case of transpose op. test=kunlun

* 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