* first version, accuracy corrected

* disable debug print

* use blockReduceSum in phi

* add UT

* add opCompat

* code style

* code refine

* bug fix

* code refine

* test fix

* bugfix

* codesytle fix

* code style

* code-style

* code-style

* code-style

* git

* style

* leave default relu in kernel

* style

* cleanup FCMKLDNN pattern

* merge conflicts

* update develop

* update develop

* add const

* rename to oneDNN and adjust attributes

* whitespace

* add cost interface

* update inferface and add unittest

* update unittest

* update inferface

* [CodeStyle][py2] remove `compat` module (to_text)

* remove some unnecessary decode

* remove to_text definition and unittest

* Revert "remove to_text definition and unittest"

This reverts commit a6b69cb8dca8b9b031ce10ea32d1040e7e0dd267.

* remove an assertion

* empty commit

* 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

* [AutoParallel] add callbacks

* fix unittest

* fix dist_context

* fix engine

* fix cmakelist

* fix unittest's returns

* fix cmakelist

* Fix bug of reduce_sum op. When input.numel() > INT32_MAX, its result
is wrong.

* Support allow_partial switch, which can be configure in
pipeline_configs. If sent tensor are not the same from
different hosts, they shouldn't been sent partially and
then concated as a whole tensor.

* Change name allow_partial to enable_partial_send_recv.

* Add global variable _enable_partial_send_recv

* 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>

* Update test_sparse_transpose_op.py

* Update test_sparse_transpose_op.py

* init gumbel api

* commit: update test file

* fix：bug

* update Gumbel API

* upgrade distribution/gumbel.py

* add tests/test_distribution_gumbel.py

* fix：code style

* fix：code style

* fix：code style

* fix：code style

* fix bug

* fix：code style

* fix：code style

* fix：rollback uniform

* fix：delete invalid code

* fix：bug and add static test

* fix：code style

* fix：code style

* fix：delete init transforms

* fix：bug

* fix：bug

* fix：code style

* fix：code style

* fix：add transforms

* fix：code style

* fix：code style

* fix：bug

* fix：bug

* fix：code style

* fix：code style

* fix：bug

* fix：code style

* fix：code style

* fix：bug for gumbel.py / add：judge transforms'len for transformed_distribution.py

* update gumbel.py

* fix：bug for test_distribution_gumbel.py

* fix：bug for test_distribution_gumbel_static.py

* fix：code style

* fix：code style

* fix：coverage

* fix：bug

* fix：bug

* fix：code style

* fix：bug

* delete：no use package for gumbel.py

* add：coverage transforms'len judge for test_distribution_gumbel.py

* fix：code style for test_distribution_gumbel.py

* fix：coverage

* fix：code style

* fix：code style

* fix：code style

* fix：code style

* fix：code style

* fix：en doc

* fix：param

* fix：copyright

* fixSample; test=document_fix
Co-authored-by: Ndasen <sen15530876201@163.com>

* 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

* first version of ln_s_p with s>0

* refine and UT

* pass opt draft

* pass opt

* code refine

* code-style

* bug fix

* fix ci test

* code style

* [Auto Parallel] Fix the bug for None labels

* [Auto Parallel] Fix the completion bug

* skip ReplaceAllReduceOp in GraphtoBlock when nccl_ctxs_ is nullptr

* update ut

* test_dist_allreduce_op failed

* fix test_dist_allreduce_op

* add ut

* fix nccl cpu compile

* fix

* [CodeStyle][py2] remove `compat` module (to_bytes)

* remove some unused imports

* clean up to_bytes definition and unittests

* Revert "clean up to_bytes definition and unittests"

This reverts commit e726539e1768172a411ff60e63fab82f164343cf.

* use `b` prefix instead of `encode()`

* add singleton to custom device

* Update custom_device.cc

Init device_init_flag_ in default

* update test_image.py

* update test_image.py

* for gpt-gen

* fix reshard

* adapt assign and shape op

* add dist_assign & unittest

* add conditional block unittest

* rename unittest

* Fix hAPI bug of not compatible with LayerHook

* fix immutable op quantize bugs

* fix

* fix build bug

* fix test

* notest,test=inference

* fix ppyoloe acc drop bugs

* fix test

* fix test

* add test

* fix

* fix

* fix test

* fix refined name bug

* fix test

* bias fix

* fix matmul weight dequant bug

* re-ci

* fix tester

* fix test

* fix tester

* update weight dequantize func

* update code

* update test for converage

* update test

* update cmake

* update cmakelist

* update code

* rerun ci

* remove useless code

Add symbolic shape deduction function for unfold, scatter_nd_add, p_norm, grid_sampler, pad3d, etc (#46291)