* Add the check of lod_level between compile-time and runtime.
test=develop

* Fix bug in check_compile_vs_runtime.
test=develop

* Fix the check of output when it is dispensiable or intermediate.
test=develop

* Share lod of x to out in match_matrix_tensor op in compile-time.

* Implement GetLoDLevel in InferShapeContext.

* Set the default value of check_compile_vs_runtime to False and enable it in test_sequence_pad_op.
test=develop

* Enable check_compile_vs_runtime in test_match_matrix_tensor.

* Add the implementation of SetLoDLevel in InferShapeContext.

* Remove the implementation of IncreaseLoDLevel and call Get/SetLoDLevel instead.

* Remove the implementation of DecreaseLoDLevel and call Set/GetLoDLevel instead.

* Refine some ops and unittests.
test=develop

* Fix a typo.
test=develop

* Remove the check of var type, and change int to int32_t.
test=develop

* Add unittest for Get/SetLoDLevel.
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

* Refine the InferShape of ReadFrom and WriteTo op, and add comment to explain why not call ShareLoD for runtime.
test=develop

* Add comment for ReorderLoDTensorByRank op.

* Add comment for lod_tensor_to_tensor_array op to explain why only call DecreaseLoDLevel for compile time.
test=develop

* ShrinkRNNMemory op should call ShareLoD for compile time.
test=develop

* Add the implementation of IncreaseLoDLevel and add the compile-time check of lod_level in InferShape of sequence_pool.
test=develop

* Refine the unittest of DynamicRNN.
test=develop

* Change PADDLE_ENFORCE to PADDLE_ENFORCE_NE.
test=develop

test=develop

test=develop

Fix code to support cpplint syntax check

test=develop

* speedup split_op
test=develop

* speedup split_op
test=develop

* rename ConcatGrad to Split

* refine concat and split
test=develop

* fix compile 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.

* Update tensor_util.h

* Update with moved TensorDesc

* Fix tensur_utils.cu

* Update

* Update

* Update

* Update

* Make tensor_util.cu a symbolic link

* Rename Tensor::CopyFrom to Tensor::Copy

* Fix CI

* Fix compile

* Rename API of DeviceContext

Make them as usual names.

* Rename API of DeviceContext

Make them as usual names.

* Fix compile

* Fix compile

* Fix compile

* Fix compile

* Fix compile

Make them as usual names.

Make them as usual names.

Make them as usual names.

* "change operator interface"

* "move devicepool to device_context"

* "fix operator test"

* "fix op_registry Run interface"

* "net op passed. Need to fix nccl multi-Context"

* "add nccl group function"

* "add nccl group function"

* "fix gpu count exceed 32 error"

* "fix recurrent op, nccl op"

* "change the other operators interface with Place"

* "fix typo"

* "fix pybind"

* "fix device in python side"

* "fix pybind failed"

* "add init for test"

* "fix CI"

* Rename XXDescBind --> XXDesc

* Fix Compile

* Move framework.proto to proto namespace

* Fix compile

* Fix compile

* Fix Compile

* "make global tensor function independently"

* "replace functor"

* "fix inline template error"

* "fix tensor array with CopyFrom"

* "fix other case use CopyFrom"

* "move the op interface hardly"

* "fix operators"

* "fix typo"

* "delete dynamic recurrent rnn and fix gru_unit in debugmode"

* "fix unique_ptr copy"

* "fix cuda copy"

* "fix namespace error"

* "removed nccl python test"

* "fix include error"

* "fix typo"

* fix copy util test

* 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

* 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

* clean code

* refactor

* use ostream

* update test

* fix gpu build error

* make gpu test pass