* Add stft_op.

* Add stft_grad_op.

* Add stft_op unittest.

* [DLTP-45176] Add complex compatibility in static mode for stft api.

* [DLTP-45176] Add complex compatibility in static mode for stft api.

* Add doc.

* Update unitests of stft op.

* Update spectral helper.

* fix coding style.

* Added BF16 to mean op

* fix for CI

* fix for CI

* fix for CI

* save InferVarType changes, test=develop

* remove code comments, test=develop

* tweak code, test=develop

* fix compilation warning, update merge_ids_op split_ids_op to new interface, test=develop

* modify fused_bn_activation_op, test=develop

* fix error of fused_bn_activation_op, test=develop

* fix PADDLE_ENFORCE and unittest coverage issue, test=develop

* tweak PADDLE_ENFORCE messages, test=develop

* improve unittest coverage, test=develop

* add StaticGraphInferVarType class, test=develop

* rebase develop branch, test=develop

* fix unittest error, test=develop

* remove comments, test=develop

* improve unittest coverage, test=develop

* imporve error message and imporve unittest coverage, test=develop

* upgrade InferVarType API, test=develop

* tweak pyfunc error message, test=develop

* fix compilation conflict - save_combine_op, test=develop

* fix error message of l2_normalize, matmul, mean, etc. 
* add the test case for those ops

* refine grad maker, test=develop

* refactor tracer stage 1, test=develop

* merge develop to solve conflict third times, test=develop

* refactor dygraph,test=develop

* fix failed unittest,test=develop

* polish code,test=develop

* check windows ci error,test=develop
try to fix windows ci error by np.allclose,test=develop

* polish vlog and profiler, test=develop

* try to fix preceding ops order,test=develop

* test transformer in windows ci, test=develop

* use python c-api to speed up tracer.trace,test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, add ut for debug string and gradient_accumulator

* test=develop, add tests for layer/gradient_accumulator/prepared_op

* test=develop, fix complie error for test_prepared_op

* test=develop, add more ut for dygraph

* test=develop, create API.spec for dygraph api change

* optimize grad maker; test=develop

* optimize grad maker

* test

* grad make optim; test=develop

* fix unittest bugs; test=develop

* add dygraph grad op maker and split_op

* grad op maker refactor; test=develop

* add dygraph grad maker; test=develop

* fix op deformable_conv_v1_op bug; test=develop

* fix deformable_conv prroi pool bugs;

* fix new op grad op maker bug; test=develop

* fix split by ref bug; test=develop

* fix dygraph auto prune bug; test=develop

* fix test_trace bug; test=develop

* fix fused emb seq pool bug; test=develop

* remove useless code in op_desc file; test=develop

* remove useless code, StrVarBaseNode; test=develop

* fix review issues; test=develop

* fix rank_loss grad maker; test=develop

* remove flag in VarBase; test=develop

* fix distributed_notify_op compile bug ; test=develop

* fix reshape op double grad; test=develop

* fix expand as op; test=develop

* add impertive type_defs.h for demo_train; test=develop

* fix inference lib cmake; test=develop

* fix inference lib; test=develop

* fix infernce_lib; test=develop

* fix inference cmake; test=develop

* fix inference lib; test=develop

* fix inference lib; test=develop

* remove condition dygraph grad maker, modify local name; test=develop

* fix split grad maker bug; test=develop

* fix pyramid_op bug; test=develop

* change travis time out limit; test=develop

* restore travis; test=develop

* change timeout limit; test=develop

* replace part of the old implementation, test=develop

* restore concat op, test=develop

* update all ops implemention & delete GetDataTypeOfVar func, test=develop

test=develop

test=develop

test=develop

* add_infer_var_type
test=develop

* InferVarTypeHelper-> VarTypeInferenceHelper
test=develop

* PassInputTypeAndDTypeOnOutput
 test=develop

* follow comment
test=develop

test=develop

* "add inplace attribute"

* "register inplace attribute"

* "change se-next model for memory-reuse"

* "fix typo"

* repick

* fix merge conflict

* "fix stupid error"

Do not use ctor

* Reduce line of codes.
* We can use virtual function for Maker now.
* The implementation does not care what maker holds, it is easier to
refactor later.

* Rename XXDescBind --> XXDesc

* Fix Compile

* Move framework.proto to proto namespace

* Fix compile

* Fix compile

* Fix Compile

There are mainly following fixes:

- take `DeviceContext` as the template parameter of math functors and OpKernel instead of `Place`
- remove `eigen_device` interface in base class  `DeviceContext`
- remove `GetEigenDevice` interface in `ExecutionContext` and base class `DeviceContext`
- remove unused `platform::EigenDeviceConverter`
- rename `REGISTER_OP_GPU_KERNEL` to `REGISTER_OP_CUDA_KERNEL`
- rename `USE_GPU_ONLY_OP` to `USE_CUDA_ONLY_OP`

* Add LoDRankTable

LoD Rank Table stores the `level` of `lod` which is ordered by sequence
length in descending order. It is useful when implement dynamic RNN and
is shared by dynamic RNN memory, dynamic RNN slice input and dynamic
RNN slice output operators.

* Add skeleton for array_to_lod_tensor and lod_tensor_to_array

* Add VarType::LoDTensorArray

* Add PyBind of LoDTensorArray

* Add InferVarType

* Add first unittest

* Add ut

* Add unittest

* Add unittest

* Add unittests

* update

* init

* add infershape for lod_tensor_to_array_op

* compelete array_to_lod_tensor_op

* copy data

* clean code

* clean code

* Fix unittest data

* fix bugs

* fix compile error

* Refine TensorToArrayOp

* refactor array_to_lod_tensor

* Unittest

* fix bugs

* Fix unittest

* Fix unittest

* debug

* Debug

* Fix unittest

* Add grad for ops

* Debug

* Fix a bug

* fix a bug

* fix a bug

* fix m_ops

* fix activation op

* Simplize Gradient Check

* Stash

* Extract apply_backward_pass to backward.py

Rename apply_backward_pass to append_backward_ops

* Use graph API to check gradient

* Fix ci

* Fix CI

* Fix backward for double precision

* Stash

* Fix CI

* Fix ci

* Ignore GRU test

* Ignore xe op

* Fix CI

* Fix softmax with xe gradient

The correct equation should be IG = OG * (d_softmax_with_xe())

* Fix typo

* Fix merge error

* Disable LRN

They are public now

* init Infershape

* add static InferShape interface

* refactor add-op infershape

* add AttrReader

* add all maker's infershape

* add all InferShape

* add python infer api

* add VarDesc interface

* add python VarDesc and OpDesc interface

* update python code

* use infershape function to do shape inference

* clean code

* do not use pointer

* refine code of op_proto_maker

* add get_dims to VarDesc

* refine the code

* remove the dependency from operator to op registry

* remove OpProtoAndCheckerMaker from operator

* restore complete_add_op

* add shape_infer_impl.h

* code optimization

* remove const return value

* add fake BlockDesc class

* optimize code

* remove infer function in op_info

* move InferShapeContextImpl to operator.h

* optimize the interface of InferShapeContextBase

* add temperary interface of new infershape

* change add_op, clip_op, conv2d_op and activation_op

* change all operators InferShape

* fix SetDim

* update cos_sim_op

* update crop_op

* update lookup_table_op

* allocate tensor when call GetDim in InferShapeContext

* update modified_huber_loss_op

* update rowwise_add_op

* update mean_op

* update sequence_avg_pool_op

* typo

* remove old InferShape interface

* can compile

* fix or unit test

* clean code

* clean code

* remove const before InferShapeContext

* change InferenceContextBase to pointer

* rename RunTime to Runtime, code clean