NetLab

Quantity breeds quality.

Machine learning engineering is highly experimental and iterative in nature. NetLab is a minimal development framework for rapid prototyping in PyTorch to make sure ideas can be validated quickly.

NetLab provides boiler plate code for training neural networks and lets you focus on the important aspects of machine learning engineering. NetLab also comes with explorative methods and useful utilities.

Usage

Training a network:

from src.modules.model import ConvNet
from src.data.dataloader import get_dataloader
from src.config.config import init_config
from src.train.train import train
from src.utils.tools import set_random_seed


def experiment_imagewoof():

    config = init_config(file_path="config.yml")
    config.dataloader.dataset = "imagewoof"

    set_random_seed(seed=config.random_seed)

    dataloader = get_dataloader(config=config)

    model = ConvNet(config=config)
    model.to(config.trainer.device)

    print(config)
    train(model=model, dataloader=dataloader, config=config)

    print("Experiment finished.")


def main():
    experiment_imagewoof()


if __name__ == "__main__":
    main()

Random Hyperparameter Search:

from src.modules.model import DenseNet
from src.data.dataloader import get_dataloader
from src.config.config import init_config
from src.train.train import train
from src.utils.tools import set_random_seed
from src.utils.random_search import create_random_config_


def experiment_random_search():

    n_runs = 1000
    n_epochs = 10

    config = init_config(file_path="config.yml")

    config.trainer.n_epochs = n_epochs
    config.dataloader.dataset = "cifar10"
    config.tag = "random_search"

    for _ in range(n_runs):

        create_random_config_(config)

        set_random_seed(seed=config.random_seed)

        dataloader = get_dataloader(config=config)

        print(config)
        model = DenseNet(config=config)
        model.to(config.trainer.device)

        train(model=model, dataloader=dataloader, config=config)


def main():
    experiment_random_search()


if __name__ == "__main__":
    main()

Cleaning up

python make_clean.py --folders data/ runs/ weights/

TODO

• Add callbacks
• Add confusion matrix

License

MIT