# Conflicts:
#	fastNLP/api/api.py
#	fastNLP/modules/encoder/variational_rnn.py

add parser API

# Conflicts:
#	fastNLP/core/dataset.py

2. metric增加SpanFMetric，可以用于计算sequence labelling的performance
3. 分词复现任务根据新版接口做了部分调整。

* refine code style

* fix failed tests

* remove conflicts
* all tests passed

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

* refine code style
* fix tests
* add a new tutorial

* add code comments
* merge *_saver.py & *_loader.py in io/
* (ancient codes) rename Loss into LossFromTorch

* clean up unused codes

* remove unused codes in metrics.py
* add tests for DataSet
* add tests for FieldArray
* add tests for metrics.py
* fix predictor, add tests for predictor
* fix bucket sampler, add tests for bucket sampler

# Conflicts:
#	test/core/test_trainer.py

2. loss中修复一个错误
3. metric中fast_param调整

* fix FieldArray type check bugs

2. trainer中update_every改为print_every, 因为update_every可能引起optimizer update的误解
3. fieldarray content支持使用np.ndarray初始化

# Conflicts:
#	fastNLP/core/dataset.py
#	fastNLP/core/trainer.py
#	test/core/test_trainer.py

Trainer support print_train and tqdm train.

* fix losses的_fast_param_map的bug
* Trainer添加sampelr初始化参数，并调整参数顺序
* refine codes

* DataSet修改__repr__，优化print(datset)的输出
* Instance修改__repr__，优化print的输出
* Optimizer优化传参提示
* Trainer去除kwargs参数
* losses.py加个参数
* 对应test code的修改

* 更新Loss的接口形参跟metric保持一致
* 添加对几种loss的测试
* embed_loader采用维度独立的方法采样
* 对应测试代码的修改

* 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

* dataset检查slice开始位置，确保结果不为空
* fieldarray检查content不为空
* optimizer接受的model params是一个generator，不能赋值
* code style refine

* improve Loss initialization interface
* improve test codes for trainer