* init

* add some check

* add dist transpile logic

* add insert op for block

* init change get_pserver_program

* optimize code

* fix a bug

* can run now

* start to do table split

* start to process table gradient

* complete pserver part

* can send_vars now

* revert cpplint

* fix a bug

* optimize code

* move dist test to models

* revert the interface of distribute_transpiler.transpile

* fix prefetch_block

* optimize trainspiler code

* add comment to sum_op

* add warning log

* fix comment

* fix test_send_recv

* fix test_send_recv

* fix train with no distributed table

* optimize GetDims

* Eagerly drop local scope in iteration

* Correct create var

* Fix typo

* Debug

* remove net op and cond_op

* fix cpplint

* fix dependency

* delete backward_test; fix compile

* disable batch_norm backward

* rm test_net.py

* make batchnorm test independent of backward.cc

* make test_layer_norm_op independent of backward.cc

* make test_layer_norm_op independent of backward.cc

* delete unused code

* clean up

* Support testing during training by ParallelExecutor.

* Add unit test.

* Improve the interface.

* Follow comments.

* Update source files.

* Update headers

* Update

* Update

* Update

* Update

* Fix a CMake dependency

* Fix cpplint issues

* Fix cpplint issues in channel.h and channel_impl.h

* Fix typo

All leaves must be variables. When all variables are ready, the
execution will be completed. If a operator has no output, the `Op::Run`
might not be started when the execution of graph has been complete.