Integrated Trainer of Parameter Server (API add `fluid.contrib.layers.sparse_embedding` only) (#22957)

* Integrated Trainer of Parameter Server

* add_dygraph_execution_context

* add dygraph infershape context and execution context; test=develop

* fix imperative bug; test=develop

* remove inputs outputs interface from execution context,
because it have same function with inputNames;
test=develop

* remove tracer_test ctest; test=develop

* fix split op bug; test=develop

* fix unitests bug; test=develop

* fix distribute test bug; test=develop

* fix ngraph compile bug; test=develop

* fix grad maker bug; test=develop

* fix load op bugs; test=develop

* fix operator.cc construct bug; test=develop

* remove useless name find in operator; test=develop

* add tracer_test; test=develop

* fix concat, split bug; test=develop

* remove tracer_test unitest; test=develop

* fix attribute check bug; test=develop

* add test code to fix converage; test=develop

* remove useless code, change check backward input in engin; test=develop

* unlock var type infer shape;test=develop

* add ShareAllLoD api; test=develop

* add dygraph infershape context unitest; test=develop

* remove increase and decrease lod in dygraph; test=develop

* addd override; test=develop

* fix increase descrease lod; test=develop

* fix paddle_enforce; test=develop

* disable lod op dygraph check; test=develop

* fix paddle enforce error; test=develop

* add comment for op_registry and OperatorBase; test=develop

* optimize the comment of op_registry; test=develop

* fix format of comment; test=develop

* fix format of comment; test=develop

* optimize the format of comment; test=develop

* optimize the format of the comment; test=develop

* optimize comment of op_registry; test=develop

* Add detailed error messages for nce layer

test=develop

* Fix some problems

test=develop

* Fix unit test coverage

test=develop

test=develop

* 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