test=develop

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.

* limit variable type to lod tensor in memory optimization transpiler

* refine policy

* support while operator

* fix random seed and training data order

* refine get_cfgs method to support multi while operators

* refine codes

* 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 InferVarType

* compelete restoring program_bind from program_desc

* Fix bugs

* fix compile errors

* fix errors and add unit tests

* rename some vars

* Follow comments

* 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

* add target to Backward, generate var in block when call backward

* modify backward_test

* fix executor_test

* set var desc default type to LOD_TENSOR

* update backward_test

* insert loss in the top level of backward

* create grad vars for all blocks in current program

* optimize code

* update test_program.py

* only create var for newly create blocks when backward

* Update VarDesc from design doc

* Fix GCC compile

* Fix unittest