* [NPU] add npu support for conv3d and conv3d_grad

* [NPU] delete failed unittests due to Ascend not support

* [NPU] delete debug codes

* [NPU] optimize codes, notest

* [NPU] remove const_cast

* [NPU] optimize for remove const_cast

* [NPU] fix written errors

* add more ops

* add authors
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NAllen Guo <alleng@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

* rm ipu_strategy.check()

* fix UT fail

* fix typo
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

* sync changes

* copy sOpNamescope

* fix UTs

* add authors
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NAllen Guo <alleng@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

* fix code-format

* fix compile error

* add comments for feed_op
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

[KP] Add unittests for brelu,ceil,celu,elu,floor,hard_shrink,hard_sigmoid,log1p,logsigmoid,relu6,silu,soft_relu,softsign,swish (#40448)

* solve unexecuted UT

* add 24 activation op UT

* append swish&thresholded_relu to kpfirst_list

* rm thresholded_relu

* add tril_triu for xpu, *test=kunlun

* add tril_triu for xpu, *test=kunlun

* add tril_triu for xpu, *test=kunlun

* add tril_triu for xpu, *test=kunlun

* add tril_triu for xpu, *test=kunlun

* add pg_hccl

* Added cuBlasLtHandle_t to device context.

* Added fused_gemm_epilogue op.

1. Added fused_gemm_epilogue op to leverage cuBlastLt Epilogue.
2. Support fusion Act(X*Y + bias), X'dims >=2 and Y'dims shoule be 2.
2. Act currently only be supported ReLU. (Will add GeLU in the future).

* Added UT to fused_gemm_epilogue op.

* Added LinearAct Pattern

1. Added LinearAct into graph_pattern_detector.* to define (2.)'s
pattern.
2. LinearAct is used to detect act(element_add(matmul_v2(x, w), bias)).
3. act currently only support ReLU (Will support GeLU in the future).

* Added FuseGemmEpiloguePass

1, Added FuseGemmEpiloguePass to handle nn.Linear + Act{ReLU}
fusion (GeLU will be supported in the future).
2. Only support matmul_v2 from nn.Linear.

* Added pybind to BuildStrageter.fuse_gemm_epilogue_.

* Added UT for fuse_gemm_epilogue_pass.

* GeLU support and EpilogueSingleton

1. Added GeLU support to fused_gemm_epilogue op.
2. Added EpilogueSingleton to cache auxiliary pointer.
3. Added related UTs.

* Rename cublaslt_epilogue_opto gemm_epilogue_op.*.

* Added both train and infer pattern to LinearAct.

1. Added support of fwd graph with grap_ops linking to LinearAct.
2. Added related changes to fuse_gemm_epilogue_pass for above
modification.

* Changed CUDA requirement from 11.4 to 11.6 for fuse_gemm_epilogue_pass.

* Added identity activation support to gemm_epilogue_op.

* Added Linear Fusion (matmul_v2 + ele_add)

1. Added matmul_v2 + ele_add pattern to LinearActPattern.
2. Added matmul_v2 + ele_add support to fuse_gemm_epilogue_pass.

* Rename gemm_epilogue_op.* to fused_gemm_epilogue_op.*

* Add fused_gemm_epilogue_grad op.

1. Added fused_gemm_epilogue_grad to support backward epilogue fusion.

* Add UTs to fused_gemm_epilogue_grad_op.

* Change attribute name in fused_gemm_epilogue_grad_op for clearing.

* Allow DX and DBias be dispensable to fused_gemm_epilogue_grad op.

* Added ElementwiseAdd+Matmul+Act graph pattern detection.

* Fuse backward of Linear( Act(x))

1. Added backward fusion pass to Linear( Act(x)).
2. Added backward fusion pass to Linear(x).

* Added UTs to backward fusion of Linear(Act(x)).

* Complete document of arguments to fused_gemm_epilogue_op.

* Made arguments of some functions pass by reference.

* Modify code with review comments.

1. Made arguments of some function pass by reference.
2. Removed redundant code.
3. Followed Google code style to change code.

* Made 'const' code style be consistent

* Fixed random seed of python UTs.

* Set Compiling constrains to cuBlasLt

1. Require CUDA 11.6+
2. Remove fuse_gemm_epilogue related tests when CUDA < 11.6.

* Code Reivew from Paddle

1. Changed arguments name is_first_gemm to without_x_gradient for
clearing.
2. Applied PADDLE_THROW in fused_gemm_epilogue_op.

* Remove EpilogueSingleton

1. Applied ReserveSpace to replace Epilogue for passing auxiliary
pointers between FWD and BWD.

* Fix a logical error and enhance UTs.

1. Added act op count checking in UTs.
2. Fix issue to fuse backward or ReLU(Linear(X)).
3. TODO: solve GELU fusion issues.

* Fix Linear and GeLU fusion issues.

1. Modified graph_detech_pattern to fit with both linear wiht gelu or
relu.
2. Modified data range in Uts to allow negative values.

* Removed fused_gemm_epilogue_op.h.

* Rename namespace pten to phi.

* Rename name of arguments in fused_gemm_epilogue_op

1. bias -> Bias.
2. out -> Out.
3. reserve_space -> ReserveSpace.

* Change EpiloguePassActivationCache as local variable.

1. Removed singleton in EpiloguePassActivationCache.
2. Made EpiloguePassActivationCache as an argument to each pass
functions.

* add softmax log_softmax

* refine rocm

* refine unittest

* add scale gather sum

* refine CUDA_ATOMIC_WRAPPER ADD for bf16

* add gather unittest

* solve conflict

* add scale uinttest

* add sum unittest

* solve conflict

* refine gather unittest

* refine unittest

* rename pten_utils to phi_utils

* rename pten_utils target

* rename Pten to Phi

* replace pten with phi

* resolve conflict

* [KP] Unify .cu and .xpu files with .kps files

* fix CI bug in GPU and modify the list

* fix conflict

* modify the date

* Fix compile error on cuda_arch less than 700.

* rename pten to phi

* fix infrt compile failed

* resolve conflict

* optimize block config  and fp16 atomicAdd perf for lookup_table_v2_grad.

* add processgroup_nccl

* [MLU] add cncl parallel context and mlu resource pool

* [MLU] fix the cncl_context_test

* add elementwise_div

* refine rocm

* refine code

* refine op register

* solve conflict

* refine unittest

* refine unittest precision

* add rocm

* fix fill_constant bug, *test=kunlun

* fix fill_constant bug,*test=kunlun

* 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

* Unify paddle/pten::framework::ddim into pten::ddim

* fix paddle namespace

* compile sucessfully

* fix npu src file

* fix conflict

* fix conflict

* fix tensorrt compiler error

* fix conflict

* fix conflict

* fix tesst file conflict

* fix conflict

* fix mlu file conflict

* fix mlu file conflict

* fix cinn header file conflict

* fix conflict

* fix conflict

* fix conflict

* fix conflict

* Update IpuStrategy

* fix ci

* rerun ci

* add softplus op for kunlun2. test=kunlun

* add softplus op for kunlun2. test=kunlun

* fix code style. test=kunlun

* fix code style. test=kunlun

* add more test cases. test=kunlun

* pten matmul cuda kernel support bf16

* fix pten kernel name

* add matmul_grad bf16 kernel

* add emptylike bf16 kernel

* fix compile

* suppport rocm

* fix error

* fix rocm

* add bf16 header file

* fix compile

* [CustomRuntime] Add DeviceManager

* [CustomRuntime] Add DeviceInterface

* [CustomRuntime] Add Stream, Event, DeviceGuard, CallbackManager

* [CustomRuntime] Add plug-in device

* [CustomRuntime] Memory module support PluggableDevice

* [CustomRuntime] Add WITH_PLUGGABLE_DEVICE cmake option

* update

* [API] update API doc based on comments, test=develop
Co-authored-by: Nqili93 <qili93@qq.com>

* #1 migrate dist-related type()-> dtype()

* move datatype function from pten -> fluid/framework

* change type() in imperative into convert(dtype())

* modify xx_tensor->type into xx_tensor->dtype

* change the set_type interface and the caller

* modify xx_tensor.type into xx_tensor.dtype

* fix mutable_data(place, dtype())

* change caller of mutable_data in pten and distributed

* change the caller of mutable_data in fluid/framework

* change the caller of mutable_data in imperative directory

* mutable_data: inference

* update the call of mutable_data

* transfer MakePenScalarArray MakePtenScalar ResetHolderWithType

* pass the compile. the next step is remove VarType in Pten

* fix all and remove VarType from pten. success in linux. Next task is other platform

* fix conflict with develop

* fix compiled error

* Fix reset conversion

* fix conflict

* fix compiled problem

* fix typo

* Fix << in tensor_utils.cc

* fix type->dtype

* fix unittest

* fix tensor init constructor

* fix DataTypeSize for BFloat16

* fix code style

* fix npu compiled error

* fix npu

* compile npu sucessfully

* fix conflict

* fix conflict
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* Rough implementation for experiment

* Support allocate cuda managed memory

* Fix CI error

* Modify UT

* Check whether support memory oversubscription

* Fix ROCM Compile error

* Fix ROCM Compile error

* Fix UT cuda_managed_memory_test

* Set UT timeout to 40

* Add UT OOMExceptionTest

* Set UT timeout to 50