Make the evaluators inside a recurrent goup true evaluator, meaning that their evaluation results are incorporated into the whole evaluator result.

No longer need to use SubsequenceInput. The framework will detect.

* also remove unused getValueStr

* Different Type compare.
* ostream << should pass a const object.
* remove always true checks.

* Different Type compare.
* ostream << should pass a const object.
* remove always true checks.

* Fix sparse training for trainer_count=1

For trainer_count=1, the gradient machine is NeuralNetwork, which does not create parameter buf for PARAMETER_GRADIENT for sparse update in Parameter::enableType. But gradient parameter buf is still used in SgdThreadUpdater.

* Minor update to comment

* hierarchical rnn document, add new config example

* update inputs_type of label

* add check for unsupported config

* refine hierarchical document

* refine doc title

* update docs, fix paddle to PaddlePaddle

* follow comments

* follow comments to fix bugs

* Correctly handling multiple inputs and integer inputs for recurrent_group

* Fix ScatterAgentLayer for generation

* Revert sequence_(nest)_rnn.conf

Sequences should be sorted according to the number of subsequences they have.

Change-Id: I8e0a8ea6fc2760652d9c76440a539c90860062d3

* modify RecurrentGradientMachine to support hasSubSeq sequence inlinks with the same number of sentence but different number of tokens for each sentence

Change-Id: Ic71f00a4bb346b4fa93e650dfb4b1a0d8d2338b0