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FengZiYjun 05af2e7544 Introduce Fields concept to eliminate the use of different sub-trainers/sub-testers. - 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		2018-09-15 19:23:10 +08:00
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README.md

fastNLP

fastNLP is a modular Natural Language Processing system based on PyTorch, for fast development of NLP tools. It divides the NLP model based on deep learning into different modules. These modules fall into 4 categories: encoder, interaction, aggregation and decoder, while each category contains different implemented modules. Encoder modules encode the input into some abstract representation, interaction modules make the information in the representation interact with each other, aggregation modules aggregate and reduce information, and decoder modules decode the representation into the output. Most current NLP models could be built on these modules, which vastly simplifies the process of developing NLP models. The architecture of fastNLP is as the figure below:

Requirements

numpy>=1.14.2
torch==0.4.0
torchvision>=0.1.8
tensorboardX

Resources

Installation

Run the following commands to install fastNLP package.

pip install fastNLP

Cloning From GitHub

If you just want to use fastNLP, use:

git clone https://github.com/fastnlp/fastNLP
cd fastNLP

PyTorch Installation

Visit the [PyTorch official website] for installation instructions based on your system. In general, you could use:

# using conda
conda install pytorch torchvision -c pytorch
# or using pip
pip3 install torch torchvision

TensorboardX Installation

pip3 install tensorboardX

Project Structure

FastNLP
├── docs
├── fastNLP
│   ├── core
│   │   ├── action.py
│   │   ├── __init__.py
│   │   ├── loss.py
│   │   ├── metrics.py
│   │   ├── optimizer.py
│   │   ├── predictor.py
│   │   ├── preprocess.py
│   │   ├── README.md
│   │   ├── tester.py
│   │   └── trainer.py
│   ├── fastnlp.py
│   ├── __init__.py
│   ├── loader
│   │   ├── base_loader.py
│   │   ├── config_loader.py
│   │   ├── dataset_loader.py
│   │   ├── embed_loader.py
│   │   ├── __init__.py
│   │   └── model_loader.py
│   ├── models
│   ├── modules
│   │   ├── aggregation
│   │   ├── decoder
│   │   ├── encoder
│   │   ├── __init__.py
│   │   ├── interaction
│   │   ├── other_modules.py
│   │   └── utils.py
│   └── saver
├── LICENSE
├── README.md
├── reproduction
├── requirements.txt
├── setup.py
└── test
    ├── core
    ├── data_for_tests
    ├── __init__.py
    ├── loader
    ├── modules
    └── readme_example.py