* add deform_conv2d,DeformConv2D

* update  lite tag.

* fix cmake error log.

* rm complexvariable

* modify test_var_base unittest

* remove duplicated codes

* Fix api docs in RNN, Transformer, layer_norm, WeightNormParamAttr.
test=develop

* Fix api doc for print in label_smooth.
test=develop

* Update api docs according to review comments.
Add name argument in RNN back.
test=develop

* fix bug,test=develop

* fix DLTP-15151, paddle.ParamAttr API

* fix DLTP-15083/DLTP-15274, paddle.nn.functionl.assign paddle.cast API

* fix DLTP-15431/DLTP-15432, paddle.static.nn.conv2d paddle.static.nn.conv2d_transpose API

* fix DLTP-15083, paddle.nn.functionl.assign API

* fix DLTP-15431/DLTP-15432, paddle.static.nn.conv2d paddle.static.nn.conv2d_transpose API

* support in_dygraph_mode for cast op, test=develop

* fix bug,test=develop

* fix doc

* fix DLTP-15431/DLTP-15432, paddle.static.nn.conv2d paddle.static.nn.conv2d_transpose API, test=document_fix

* fix gpu emb out of range

Change-Id: I5794ac73bd634d5ea069a6fbbd914274b6d6b7bf

* fix doc

Change-Id: I5a3350b2930a9ab2f52116c192b087307faf8fdf

* enhance array_to_lod_tensor_op lod_tensor_to_array_op errors information. test=develop

* fix format. test=develop

* format fix. test=develop

* add lod_rank_table. test=develop

* fix format. test=develop

* fix doc info. test=develop

* fix np error

* add unbind dygraph api. test=develop

* fix unbind doc.test=develop

[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

* fix multiple documentation error, test=document_fix

* fix more rst syntax errors, test=document_fix

* fix format issues in docstring, test=document_fix

* fix tensorrt output shape error

* fix unittest tensorrt_engine_op_test

* fix code style for unitest

* use has_grad instead of train_mode

* add vlog for debug

* fix ut

* fix ut

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

* fix the warning of reducer (#29323)

* fix warning of fleet (#29317)

* Fix doc of fleet api (#29282)

* 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.

* fix DATA_HOME path in win

Cherry-pick of PR #29226

fix nll_loss doc;test=document_fix