Metadata-Version: 1.2
Name: DLCreator
Version: 0.1.5
Summary: One-line command to generate a deep learning folder structure and code template!
Home-page: https://github.com/nghuyong/DLCreator
Author: nghuyong
Author-email: nghuyong@163.com
License: MIT Licence
Description: <h1 align="center">DLCreator</h1>
        <p align="center">One-line command to generate a deep learning folder structure and code template！</p>
        
        <p align="center">
          <a href="https://github.com/nghuyong/DLCreator/stargazers">
            <img src="https://img.shields.io/github/stars/nghuyong/DLCreator.svg?colorA=orange&colorB=orange&logo=github"
                 alt="GitHub stars">
          </a>
          <a href="https://github.com/nghuyong/DLCreator/issues">
                <img src="https://img.shields.io/github/issues/nghuyong/DLCreator.svg"
                     alt="GitHub issues">
          </a>
          <a href="https://github.com/nghuyong/DLCreator/">
                <img src="https://img.shields.io/github/last-commit/nghuyong/DLCreator.svg">
          </a>
          <a href="https://github.com/nghuyong/DLCreator/blob/master/LICENSE">
                <img src="https://img.shields.io/github/license/nghuyong/DLCreator.svg"
                     alt="GitHub license">
          </a>
        </p>
        
        
        <h2 align="center">What is it</h2>
        When you start a new deep learning project, are you still worrying about how to organize a project structure and writing many duplicate codes every time ?
        
        **DLCreator** is made ! It is a one-line command tool, which will automatically generate the entire folder structure and code template including data loading; model training; configuration; logs; visualization; etc.
        **So, All YOU NEED TO DO is just design your model and write some code snippet**.
        
        <h2 align="center">Install</h2>
        
        Install it via `pip`.
        
        ```bash
        pip install DLCreator
        ```
        
        :point_up: The command can be running on both Python 2 and 3.
        
        
        <h2 align="center">Getting Started</h2>
        Start a new deep learning project, just from this:
        
        ```bash
        DLCreator <tensorflow|pytorch|keras> <project-name>
        ```
        Take `DLCreator pytorch test` as an example, The same directory will generate a `test` directory, the structure is as follows:
        ```
          test/
          │
          ├── train.py - main script to start training
          ├── test.py - evaluation of trained model
          ├── config.json - config file
          │
          ├── base/ - abstract base classes
          │   ├── base_data_loader.py - abstract base class for data loaders
          │   ├── base_model.py - abstract base class for models
          │   └── base_trainer.py - abstract base class for trainers
          │
          ├── data_loader/ - anything about data loading goes here
          │   └── data_loaders.py
          │
          ├── data/ - default directory for storing input data
          │
          ├── model/ - models, losses, and metrics
          │   ├── loss.py
          │   ├── metric.py
          │   └── model.py
          │
          ├── saved/ - default checkpoints folder
          │   └── runs/ - default logdir for tensorboardX
          │
          ├── trainer/ - trainers
          │   └── trainer.py
          │
          └── utils/
              ├── util.py
              ├── logger.py - class for train logging
              ├── visualization.py - class for tensorboardX visualization support
              └── ...
          ```
        
        
        <h2 align="center">TODOs</h2>
        
        - [ ] Support tensorflow
        - [ ] Support pytorch
        - [ ] Support keras
        - [ ] Release a version to pypi
        
        
        <h2 align="center">Acknowledgments</h2>
        This project is inspired these projects:
        
        - [Tensorflow-Project-Template](https://github.com/MrGemy95/Tensorflow-Project-Template)
        - [pytorch-template](https://github.com/victoresque/pytorch-template)
        - [Keras-Project-Template](https://github.com/Ahmkel/Keras-Project-Template)
        
        
        
Keywords: deep learning,tool
Platform: any
Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*
