* fix correctness of the communicator

* fix a bug in send thread when sending var context is empty, test=develop

* add lookup_table_prefetch_op and prefetch optimize, test=develop

* remove remote prefetch GPU supported

* word2vec force with CPU, test=develop

* test dist remote lookup table force with CPU, test=develop

test=develop

* nce add check sample lables, test=develop

test=develop

* Fix truncated normal.

* Fix.

* Make nce support more distribution.

* Fix API.spec.

* Fix python API.

* Fix.
test=develop

* Fix API.spec
test=develop

* Fix sampler.

* Fix order of arguments in python API.
test=develop

* NCE add selectedrows support

* NCE update weighted sampling

* fix bugs in nce_op, and assign_value_op optimized

* fix bugs in nce_op, revert assign_value_op

* nce_op optimize

* nce_op optimize

* nce_op optimize

* add selectedRows test later

test=develop

* add selectedRows supported

* add selectedRows supported

test=develop

* add selectedRows supported

* add nce selectedRows supported, test=develop

* add nce selectedRows supported

* add nce selectedRows supported, test=develop

* fix height in nce, test=develop

* add ut

* add ut, test=develop

* make AutoGrownIndex inline
test=develop

* fix tinny error, test=develop

* Fix truncated normal.

* Fix.

* Make nce support more distribution.

* Fix API.spec.

* Fix python API.

* Fix.
test=develop

* Fix API.spec
test=develop

* Fix sampler.

* Fix order of arguments in python API.
test=develop

* Fix CPPLint errors in multiclass_nms, nccl, nce, reduce and save_load_combine

* Fix

* also div num_samples when return cost of nce_op

There are mainly following fixes:

- take `DeviceContext` as the template parameter of math functors and OpKernel instead of `Place`
- remove `eigen_device` interface in base class  `DeviceContext`
- remove `GetEigenDevice` interface in `ExecutionContext` and base class `DeviceContext`
- remove unused `platform::EigenDeviceConverter`
- rename `REGISTER_OP_GPU_KERNEL` to `REGISTER_OP_CUDA_KERNEL`
- rename `USE_GPU_ONLY_OP` to `USE_CUDA_ONLY_OP`

1. Remove checking for num_neg_samples.
2. Fix dims of Output(Cost) and Input(Bias).
3. Renamed num_sampled_classes to num_neg_samples.
4. Add TODO for add more distribution sampler.
5. Init grad_data of bias by zero.
6. Refine comments.
7. Register a kernel for type double.

1. Add nce forward and backward kernel for CPU