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* 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 |
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fastNLP
FastNLP is a modular Natural Language Processing system based on PyTorch, built for fast development of NLP models.
A deep learning NLP model is the composition of three types of modules:
For example:
Requirements
- numpy>=1.14.2
- torch>=0.4.0
- tensorboardX
Resources
Installation
Run the following commands to install fastNLP package.
pip install fastNLP
Project Structure
| module type | functionality | example |
| encoder | encode the input into some abstract representation | embedding, RNN, CNN, transformer |
| aggregator | aggregate and reduce information | self-attention, max-pooling |
| decoder | decode the representation into the output | MLP, CRF |
| fastNLP | an open-source NLP library |
| fastNLP.api | APIs for end-to-end prediction |
| fastNLP.core | data representation & train/test presedure |
| fastNLP.models | a collection of NLP models |
| fastNLP.modules | a collection of PyTorch sub-models/components/wheels |
| fastNLP.io | readers & savers |