Add weight initialization for models.

- apply DataSet in Predictor; remove sub-predictors; add "task" argument to specify which task to predict, as how Trainer/Tester did.
- remove Action class
- add helper function for DataSet, to create DataSet easily
- more code comments
- clean up unnecessary codes
- add unit tests for Batch, Predictor, Preprocessor, Trainer, Tester

- update LabelField's to_tensor method to support int & str single label
- update preprocessor's convert_to_dataset method to support single label inputs
- introduce "task" in Trainer/Tester's data_forward, Tester's evaluate and metrics methods
- in cnn_text_classification.py, change the name of the argument of forward
- in sequence_modeling.py, change the name of the argument of forward
- minor adjustments in test codes
- text_classify.py works

- add DataSet, Instance, Field to represent data in different levels
- encapsulate batching method in Batch class
- modify samplers in action.py to fit Batch
- preprocessor.run returns DataSet, instead of list
- Use Batch in Trainer/Tester
- add required_arg "task" in Trainer/Tester
- remove SeqLabelTrainer/SeqLabelTester dependencies successfully. They empty classes to deprecate.
- modify SeqLabeling model, add another argument in forward, in order to compute mask inside model
- test\model\seq_labeling.py works

format test folder

add mathjax and update pictures

update

add config saver

add requirements: tensorboardX

merge

add tensorboardX for loss visualization

Text Classification Interface

- fix issue #58, use path.join instead of +
- modify description and version in setup.py
- docstring in core/ follows RestructureText format

CWS+POS tag interface

Rewrite classification model and add initialization for conv_maxpool module

update docs

move example to docs