* 升级parser API和模型
* update docs: add new pages for tutorials
* upgrade CWS api download source
* add a new method for dataset field access
* add introduction for bert
* add more unit tests for api/processor
* remove unused test data. Add new test data.

* add DataSet.get_field(), to fetch a FieldArray based on its name
* remove old tutorials & add new tutorials

* 更新测试代码，跑通所有测试，覆盖率65%
* refine代码规范和某些注释
* fix tester self.use_cuda未赋值先使用的bug
* 添加tutorial样例数据——tutorial_sample_dataset.csv
* 【unsolved】embed_loader在计算np.cov时遇到segmentation fault

* 添加fast_load_embedding方法，用vocab的词索引pre-trained中的embedding
* 如果vocab有词没出现在pre-train中，从已有embedding中正态采样

Update embed_loader:
* add fast_load_embedding method, to index pre-trained embedding with words in Vocab
* If words in Vocab are not exist in pre-trained, sample them from normal distribution computed by current embeddings

- DataSet's __init__ takes a function as argument, rather than class object
- Preprocessor is about to remove. Don't use anymore.
- Remove cross_validate in trainer, because it is rarely used and wired
- Loader.load is expected to be a static method
- Delete sth. in other_modules.py
- Add more tests
- Delete extra sample data

2. changes of names:
  aggregation ----> aggregator
  interaction ----> interactor
  action.py ----> sampler.py
  BasePreprocess ---> Preprocessor
  BaseTester ----> Tester
  BaseTrainer ----> Trainer
3. add more code comments
4. fix bugs in predictor's data_forward
5. in sampler.py, remove Bachifier, fix some codes. but not test
6. remove unused codes in other_modules.py & utils.py
7. update fastnlp.py with new config file names and code comments
8. add data examples in data_for_tests/

- add Loss, Optimizer
- change Trainer & Tester initialization interface: two styles of definition provided
- handle Optimizer construction and loss function definition in a hard manner
- add argparse in task-specific scripts. (seq_labeling.py & text_classify.py)
- seq_labeling.py & text_classify.py work

- fastNLP interface for sequence labeling works
- fastNLP interface for text classification works

- rename "POSTrainer" to "SeqLabelTrainer"
- add text classification test data
- update make_batch in  Trainer and Tester

- [model] optimize cuda support in seq labeling model
- [test] add test data "pku" for chinese word seg
- test_tester.py and test_cws.py is OK to run!

- [tester][trainer] add cuda support
- [preprocess] fix label2index for padding label seq
- update README.md
- [test] add test_tester.py
- rename "action" to "core"

- [trainer]rename "batchify" to "make_batch" in trainer
- [trainer]pack (batch_x_pad, seq_len) into batch_x in make_batch for seq labeling, because seq length before pad is needed to make masks
- [trainer]unpack it in data_forward
- [model]shorten model definition
- [inference]build inference class. test_POS_pipeline.py is OK to infer
- [preprocessor]handle pickles in a nicer manner
- [FastNLP] add fastNLP.py as high-level API, not finished yet

optimize evaluation output in Trainer;
keep POS pipeline (loader + trainer + tester + saver) OK;
add codes borrowed from FudanParser.

- add people.txt in data_for_tests
- To do: incorrect CRF param in POS_pipeline