* Update scope.h

* typo

* Update dense_tensor.inl

* [Auto Parallel] Move the distributed info from python to c++

* [Auto Parallel] Add dist_attrs for VarDesc and OpDesc

* [Auto Parallel] Add the lost file

* [Auto Parallel] Make the dist attr be unique_ptr

* [Auto Parallel] Add the proto conversion

* [Auto Parallel] Improve the proto support

* [Auto Parallel] Fix the bugs for adding a device or a link

* [Auto Parallel] Add the C++ ProcessMesh and DistributedMapper

* [Auto Parallel] Improve the impl of these dist attrs

* [Auto Parallel] Pybind11 ProcessMesh and DeviceMesh

* [Auto Parallel] Fix the unittest problem

* [Auto Parallel] Explicitly add the src file for auto_parallel target

* [Auto Parallel] Add the proto depedency explicitly

* [Auto Parallel] Fix the cmake bug on windows and mac

* [Auto Parallel] Remove the pybind11 header file in process_mesh.h

* [Auto Parallel] Remove unused codes

* [Auto Parallel] Check whether the dist attr is null

* [Auto Parallel] Implement the assign operator for OpDesc explicitly

* fix proto bug

* add ut

* reset need_update for var_desc

* refine code

* fix var desc order issue

* Rename BOOST_GET macros

* Fix conflicts

* boost::variant -> paddle::variant

* boost::variant.apply_visit -> paddle::visit

* Update pybind_boost_hraders.h

* Fix CINN compilation errors

* Revert FetchResultType

* add new API: paddle.clone;Tensor.element_size;nn.utils.parameters_to_vector

* fix comment

Add Tokenizer related functionalities for Transformer model in order that the process of training and predicting is consistent.

* support the text string as an input Tensor
* support the "VOCAB"unordered_map<wstring, int> as an input Tensor to lookup tokens
* Tokenizer used for BERT. This tokenizer applies an end-to-end, text string to wordpiece tokenization.
* It first applies basic tokenization, followed by wordpiece tokenization.

* add auto_parallel apis

* use iwyu clean include second time, test=develop

* use iwyu clean include, test=develop, test=win

* compilation error, test=develop

* fix compilation error2, test=develop

* fix compilation error3, test=develop

* fix compilation error4, test=develop

* fix compilation error5, test=develop

* fix compilation error6, test=develop

* fix compilation error7, test=develop

* fix compilation error8, test=develop

* fix compilation error8, test=develop

* fix compilation error10, test=develop

* fix compilation error11, test=develop

test=develop

test=develop

Fix code to support cpplint syntax check

test=develop

test=develop

* Adding set_capacity method support

* Adding Python for make_channel

* Updating notest_concurrency

* Write python for make_channel method

* Write python for make_channel method

* Fix make_channel and test

* Placeholder ops for channel send, recv and close

* Adding ToTypeIndex method to var_type.h

* Add var_type.h to channel:

* Added POD_Type to the method

* Add CHANNEL to executor

* Updated get and set DataType to accomodate Channels

* Updating get and set to incorporate channels

* Adding CHANNEL as supported VarType in protobuf

* Removing unecessary import

* Fixing VarDesc to adapt to Channel as VarType

* Add channel.h to executor

* Remove innclude from channel

* Updated var_type to support Channel as  var type

* Adding get_channel to pybind

* Added ChannelHolder

* Adding make_channel as an op

* Adding ChannelHolder in channel

* Fixing typo

* Commenting out operators in concurrency

* Removing totypeid right now since we don't need it.

* Reverting python changes

* Fixing typo in framework.py

* Modify comments for ReaderHolder

* Move Pod Types from DataType enum to Type enum

* Fixed data_type.h

* Fix type in TensorDesc

* Add comment to framework.proto

* Fixed type in data_type.h

* Updated format of type in data_type.h

* Fix var_desc.h

* Fix op_kernel_type.h

* Fixed data_type_transform_test.cc

* Fix operator.h

* Fixed data_type_transform.cc

* Fixed op_kernel_type_test.cc

* Fix operator.cc

* Fixed data_layout_transform_test.cc

* Fix var_desc.cc

* Fixed assign_value_op.cc

* Fixed assign_value_op.h

* fixed protobuf.cc

* Fix data_layout_transform_test.cc and op_kernel_type_test.cc

* Fixed rnn_memory_helper_op.cc

* Fix progrma_desc_test.cc

* Fixed fill_constant_batch_size_like_op.cc

* Fix operator_test.cc

* Fixed fill_constant_op.cc

* Fixed gaussian_random_op.cc

* Fixed uniform_random_op.cc

* Fixed edit_distance_op.cc

* Fixed fill_constant_batch_size_like_op.cc

* Fixed rnn_memory_helper_op.cc

* Fixed chunk_eval_op.cc

* Fixed assign_value_op.cc

* Fixed assign_value_op.h

* Fixed cast_op.h

* Fixed cast_op.h

* Fix fill constant op

* Fixed clang for assign_value_op.cc

* Fix one_hot_op.h

* Fix one_hot_op.cc

* Fix fill_op.cc

* Fixed sum_op.cc

* Fixed sum_op clang

* Fix uniform_random_op.cc

* Fix gaussian_random_op.cc

* Fix backward.cc

* Fix protobuf.cc

* Fixed prune_test.cc

* Fixed op_registry_test.cc

* Fix data_device_transform_test.cu

* Fix travis error

* Fixed one_hot_op.cu

* Fixed op_registry_test.cc

* Fixed nccl_op.cc

* Fixing python tests

* Revert "Fixing python tests"

This reverts commit fccaa4c5.

* Fixing Pybind to remove data type

* Fixing tensor.py

* Updated the new files:

* Resolve error in merge conflict of fill_constant_batch_size_like_op.cc

* Refine Type system

* Fixing type inference

* Fixed create_reader_op.cc

* Fix var_desc.h

* Fixed executor.cc

* Fix shape_inference.h

* Fixed create_reader_op.cc

* Fix tensor_util.h

* Fixed var_type_inference_test.cc

* Fix shape_inference.cc

* Fixed sum_op.c

* Fixed read_op.cc

* Fix var_type.h

* Fixed beam_search_decode_op.cc

* sendrecvop_utils.cc

* Fix operator.cc

* Fixed lookup_table_op.cc

* Fixed op_desc.cc

* Fixed get_places_op.cc

* Fixed lod_rank_table_op.cc

* Fixed beam_search_op.cc

* Fix var_desc.cc

* Fixed lod_tensor_to_array_op.cc

* Fixed while_op.cc

* Fix program_desc_test.cc

* tensor_array_read_write_op.cc

* Fix assign_op.cc

* Fix executor.cc

* Fix protobuf.cc

* Fix protobuf.cc

Add a new type `Reader` for `VarDesc`, which can holds more than one
LoDTensor.

feature/parallel_gpu

* Rename XXDescBind --> XXDesc

* Fix Compile

* Move framework.proto to proto namespace

* Fix compile

* Fix compile

* Fix Compile

* 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

* Use stable_sort in lod_rank_table

It is easy to debug and test when use `stable_sort`and the time
complexity is not changed.

* Add LoDTensorArray

* init

* ensure ids in lookup table op must be a column vector

* add book4 configuration in test_layers

* debug test_book4

* add test_word2vec

* follow comments

* follow comments

* Update VarDesc from design doc

* Fix GCC compile

* Fix unittest