* fix load bug and add distributed strategy from pslib

* add unittest

* use cvm config

* trainer and worker config

* add unittest

* add unittest

* add test

* code style

* default accessor and multi table config

* add unittest

* add unittest

* delete print

* test

* test

* rm test

* update

* update

* update

* add unittest

* update

* update save

* add trainer desc config to distributed strategy

* code style modified

* add model parallel support in dygraph

* support control flow

* supoort sync_parameters_buffers

* fix the bug of sparse embedding

* remove the send/recv of tensor size, but users have to specify the shape of the received var explicitly.

* add adaptivelsgd

* Todo fix the code to avoid the conflict.

* rm auto from localsgd

* refine launch and distributed repr string for print

* add cudnn related strategies to DistributedStrategy

* add feature to fleet2.0 role_maker, distribute_strategy, test=develop

* move paddle.fleet to paddle.distributed.fleet

* add paddle.fleet.AsyncOptimizer
Co-authored-by: Ndongdaxiang <dongdaxiang@baidu.com>

* split meta optimizer files
* add graph execution in execution, update two properties in DistributedStrategy, unit tests for these features

* refine strategy compiler and meta optimizers
make async as a_sync

* add more settings for distributed strategy
Basically, DistributedStrategy has several parts of configurations:
- BuildStrategy: the same as paddle.fluid.BuildStrategy, but the distributed arguments are moved out of BuildStrategy
- ExecutionStrategy: the same as paddle.fluid.ExecutionStrategy
- collective communication configs: nccl_comm_num, hierarchical allreduce and so on
- distributed algorithms: async_update(mainly used in PS), lars, lamb and so on

refactor fleet api under paddle.fleet
update DistributedStrategy

test=develop

* add paddle.fleet.DistributedStrategy for 2.0