Metadata-Version: 2.1
Name: fastNLP
Version: 0.0.2
Summary: Deep Learning Toolkit for NLP
Home-page: https://github.com/fastnlp/fastnlp
Author: Fudan FastNLP Team
Author-email: fudanfastnlp@gmail.com
License: UNKNOWN
Description: # fastNLP
        
        [![Build Status](https://travis-ci.org/fastnlp/fastNLP.svg?branch=master)](https://travis-ci.org/fastnlp/fastNLP)
        [![codecov](https://codecov.io/gh/fastnlp/fastNLP/branch/master/graph/badge.svg)](https://codecov.io/gh/fastnlp/fastNLP)
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        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:
        
        ![](https://github.com/fastnlp/fastNLP/raw/master/fastnlp-architecture.jpg)
        
        
        ## Requirements
        
        - numpy>=1.14.2
        - torch==0.4.0
        - torchvision>=0.1.8
        - tensorboardX
        
        
        ## Resources
        
        - [Documentation](https://fastnlp.readthedocs.io/en/latest/)
        - [Source Code](https://github.com/fastnlp/fastNLP)
        
        ## Installation
        Run the following commands to install fastNLP package.
        ```shell
        pip install fastNLP
        ```
        
        ### Cloning From GitHub
        
        If you just want to use fastNLP, use:
        ```shell
        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:
        ```shell
        # using conda
        conda install pytorch torchvision -c pytorch
        # or using pip
        pip3 install torch torchvision
        ```
        
        ### TensorboardX Installation
        
        ```shell
        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
        
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
