torch-kerosene 0.1.0

Deep Learning framework for fast and clean research development with Pytorch

Kerosene

Deep Learning framework for fast and clean research development with Pytorch - see the doc for more details.

MNIST Example

Here is a simple example that shows how easy and clean it is to train a simple network. In very few lines of code, the model is trained using mixed precision and you got Visdom + Console logging automatically. See full example there: MNIST-Kerosene

if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    CONFIG_FILE_PATH = "config.yml"

    model_trainer_config, training_config = YamlConfigurationParser.parse(CONFIG_FILE_PATH)

    train_loader = DataLoader(torchvision.datasets.MNIST('./files/', train=True, download=True, transform=Compose(
        [ToTensor(), Normalize((0.1307,), (0.3081,))])), batch_size=training_config.batch_size_train, shuffle=True)

    test_loader = DataLoader(torchvision.datasets.MNIST('./files/', train=False, download=True, transform=Compose(
        [ToTensor(), Normalize((0.1307,), (0.3081,))])), batch_size=training_config.batch_size_valid, shuffle=True)

    # Initialize the loggers
    visdom_logger = VisdomLogger(VisdomConfiguration.from_yml(CONFIG_FILE_PATH))

    # Initialize the model trainers
    model_trainer = ModelTrainerFactory(model=SimpleNet()).create(model_trainer_config, RunConfiguration(use_amp=False))

    # Train with the training strategy
    trainer = SimpleTrainer("MNIST Trainer", train_loader, test_loader, model_trainer) \
        .with_event_handler(PrintTrainingStatus(every=100), Event.ON_BATCH_END) \
        .with_event_handler(PrintModelTrainersStatus(every=100), Event.ON_BATCH_END) \
        .with_event_handler(PlotAllModelStateVariables(visdom_logger), Event.ON_EPOCH_END) \
        .with_event_handler(PlotGradientFlow(visdom_logger, every=100), Event.ON_TRAIN_BATCH_END) \
        .train(training_config.nb_epochs)

Contributing

How to contribute ?

• Create a branch by feature and/or bug fix
• Get the code
• Commit and push
• Create a pull request

Branch naming

Feature branch

feature/ [Short feature description] [Issue number]

Bug branch

fix/ [Short fix description] [Issue number]

Commits syntax:

Adding code:

+ Added [Short Description] [Issue Number]

Deleting code:

- Deleted [Short Description] [Issue Number]

Modifying code:

* Changed [Short Description] [Issue Number]

Merging code:

Y Merged [Short Description] [Issue Number]

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