* Add complex dtype op (add) test example (#29603)


* add op test case for complex

* polish code details

* add xpu set constant support

* fix argument rror

* remove useless pyc file

* [Complex] Add real & imag op and api for complex tensor (#29672)

* add complex real op & api & unittest

* add imag op & api & unittest

* refactor op impl

* revert simplify writing due to complile failed

* polish details

* polish grad op code

* add conj op for complex types (#29527)

* add conj op for complex types

* add conj for complex types

* add more test case

* add conj_op test

* modify conj api and impl

* add complex type for fill_constant_op xpu

* add setConstant for complex type

* remove complex conj test file

* user define grad for test_conj_op

* add test case for static mode of conj api

* modify conj doc

* change input args name to x

* remove useless codes

* conj support real types

* add conj test case for real number
Co-authored-by: Nchentianyu03 <chentianyu03@baidu.com>

* Fix the dowanload bug in the case of multiple machines (#29551)

* fix the dowanload bug
* add sort for ips

* Fix bug of matmul_v2 for broadcast case (#29599)

* fix bug of matmul_v2 for broadcast

* Rebuild group automatically in dynamic graph distributed (#29255)

* add tensor_indices in AssignGroupBySize

* add rebuild group in reducer

* fix error message of gather nd (#29521)

* fix expand && concat/transpose to new api

* update xpu_header

* update activation op on kunlun

* update activation op on kunlun

* update activation op on kunlun

* update activation op on kunlun

* update activation op on kunlun

* add nearest_interp on kunlun

* update error message

* remove addcmul

* remove unittest and other related code of addcmul

* fix bug

* fix merge conflict

Fix Layer train eval setting failed in static mode, more details please see #29540

* fix wmt14 doc, remove backward, add bidirect direction in rnn api

* fix rnn unittest

* fix test_rnn_nets_static.py bug

* support roi_align & affine_channel for kunlun

* minor

* support mobilenet for kunlun (#29458)

* add xpu ops for training transformer in kunlun (#29539)

* 1.fix matmul bug 2. add one hot

* add xpu error msg
Co-authored-by: Nprocr <procrboo@gmail.com>
Co-authored-by: Ntaixiurong <taixiurong@126.com>

* add deformable_conv op on xpu (#29234)

* rebase develop

* update deformable_conv op on xpu

* update deformable_conv op on xpu

* update kunlun conv2d/softmax/elementwise implemetation (#29229)

* update conv2d & softmax to new xpu api
* test=kunlun

* remove useless comments
* test=kunlun

* remote softmax xpu op
* test=kunlun

* update kunlun softmax
* test=kunlun

* update xpu unitest
* test=kunlun

* fix elementwise_grad bug for kunlun
*test=kunlun

* support global pooling for kunlun (#29293)

* test=kunlun

* update reduce_sum op on xpu (#29367)

* update reduce_sum op on xpu

* update reduce_sum op on xpu

* support running on xpu

* fix expand/uniform_random && concat/transpose to new api on xpu (#29280)

* fix expand && concat/transpose to new api

* update uniform_random_op

* update xpu_header

* 1. fix elementwise ops'bug 2. fix softmax_with_cross_entropy_op 3. add biliner_interp_op (#29448)
Co-authored-by: Nroot <root@bjhw-sys-rpm0223.bjhw.baidu.com>
Co-authored-by: N卖鱼的哲学 <tangzhiyi11@users.noreply.github.com>
Co-authored-by: NQingshuChen <qingshu.chen714@gmail.com>
Co-authored-by: Ntaixiurong <taixiurong@126.com>
Co-authored-by: Nroot <root@bjhw-sys-rpm0223.bjhw.baidu.com>

* fix the bug of reducer in embedding

* update, test=develop (#29331)

* fix tensorrt unittest precision error

* fix unittest precision error. test_trt_subgraph_pass && test_trt_dynamic_shape_transformer_prune

* add deform_conv2d,DeformConv2D

* rm complexvariable

* modify test_var_base unittest

* remove duplicated codes

[cherri-pick] Fix bug: delete wrong check_type of paddle.concat and support LoDTensorArray (#29306) (#29368)

* fix random failed of complex matmul

* Make transpose, trace, kron, reshape, sum op support complex type (#29321)

* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types

* add test cases for complex elementwise, matmul and getitem unittest

* add test cases for complex types

* add test cases for complex matmul unittest

* kron, reshape, transpose support complex types

* sum and trace op support complex types

* add test case of sum and trace op

* fix the bug of imag part of complex not initialized

* format file

* format code style

* kron support type promotion; modify test cases

Reduce exception type so that if covert_to_static failed, it reports right error message.

[cherry-pick 2.0rc1][inplace] Add ShareHolderWith for class Variable and SharePlaceholderWith in VarBase.detach() to share the same Tensor/SelectedRows (#29267) (#29359)

[cherry-pick 2.0rc1][Dy2Stat] Fix bug: Do not use gast.Subscript to replace gast.Name in when transforming for_enumerate_loop (#29310) (#29361)

* basic impl of type promote

* add comment & another testcase

* fix complex bugs & support python op promote type

* fix failed unittests & polish code

* add unittest for coverage

* change to only promote complex type

* polish code details

* polish several comments

[Cheery-Pick 2.0.0-rc1][Dy2stat] Add a decorator paddle.jit.not_to_static to support that not to convert a function in Dynamic-to-Static. (#29253) (#29340)

Usage scenarios：A function could have run successfully in static mode,  you can use it to decorate a function in the following cases:
  1. An unknown error occurs in the dynamic-to-static conversion process of the function;
  2. In the internal implementation of the function, it has two branches: dynamic branch and static branch;
  3. Users don't want to convert the function in the process of dynamic to static.

* use has_grad instead of train_mode

* add vlog for debug

* fix ut

* fix ut

* move temporal_shift to functional

* Change the api of DataParallel and Fleet (#29224)

* Add pure fp16 training with master weights. (#27712)

* add the weight decay func for the momentum op

* Add the multi_precision function in Momentum Optimizer.

* Make sure that the initial value of master weights are same with the fp16 weights.

* add static loss scaling.

* add the rescale_grad function in the pure fp16 training.

* use the original momentum updating method.

* Polish some codes, such as variable names.

* add docstring for apis.

* update the var creation details of _create_master_weight.

* not modify codes about imperative momentum updating.

* Fix the error of test_dist_sparse_tensor_load_momentum UT.

* add unit test for multi precision fp16 training.

* add more unit tests for CI.

* Use lower threshold values for allclose comparing in test_multi_precision_fp16_train UT.

Cherry-pick of PR #29226

* hot fix complle failed in gcc4.8

* fix failed unittest

* add lamb optimizer and unittest

* fix momentum resume training

* fix momentum acc

* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types

* add test cases for complex elementwise, matmul and getitem unittest

* add test cases for complex types

* add test cases for complex matmul unittest

* The leaf tensor concept is exposed and the gradient accumulation of leaf tensor

* The leaf tensor concept is exposed and the gradient accumulation of leaf tensor

* fix coverage

* fix api doc

* fix CI unittest

* fix CI unittest

* fix unitest

* empty tensor does’t need inner_var_

* fix some error message

* fix paramete prefetch & device guard
Co-authored-by: NMrChengmo <cmchengmo@163.com>
Co-authored-by: Nchengmo <chengmo@baidu.com>

* Add a class TensorInplaceVersion to count the inplace version and put it in framework::Tensor instead of Allocation or Variable.

* Add a new attribute `_inplace_version` for VarBase.

* Raise exception if an inplace operation can result in incorrect gradient computation.

* Add a new interface _bump_inplace_version() for VarBase to bump the version whenever the Tensor is modified through an inplace operation.

* For api assign, call _bump_inplace_version() when it's an inplace operation inn dynamic mode.

* Use original var_wrapper if the inplace_version is not changed.

* Replace SnapshotVarWrapperList with SnapshotVarWrapper to optimize performane.