https://github.com/roma-glushko/morty

🔬 Lightweight experiment and configuration manager for small ML/DL projects and Kaggling
https://github.com/roma-glushko/morty

deep-learning experiment-management experiment-monitor experiment-tracking keras machine-learning pytorch tensorflow

Last synced: 10 days ago
JSON representation

🔬 Lightweight experiment and configuration manager for small ML/DL projects and Kaggling

• Host: GitHub
• URL: https://github.com/roma-glushko/morty
• Owner: roma-glushko
• Created: 2021-01-22T12:28:45.000Z (almost 4 years ago)
• Default Branch: master
• Last Pushed: 2021-12-05T19:50:36.000Z (almost 3 years ago)
• Last Synced: 2024-10-10T19:39:23.752Z (27 days ago)
• Topics: deep-learning, experiment-management, experiment-monitor, experiment-tracking, keras, machine-learning, pytorch, tensorflow
• Language: Python
• Homepage:
• Size: 1000 KB
• Stars: 5
• Watchers: 3
• Forks: 0
• Open Issues: 16
• Metadata Files:
  • Readme: readme.md

Awesome Lists containing this project

README

        
# Morty



Morty is a lightweight experiment and configuration manager for small ML/DL projects and Kaggling.

Main Features:

- **Configuration Management**. Morty includes a config loading system based on the python files that makes you configure a wide variety of moving parts quickly and without overheads.

- **Experiment Management**. Morty provides a flexible, simple and local experiment management system that tracks a lots of context about your project state to make it possible to reproduce experiments.

## Installation

```bash

pip install morty

# or

poetry add morty

```

## Example of Usage

Trains a Keras model on MNIST:

```python

import numpy as np

from tensorflow import keras

from tensorflow.keras import layers

from examples.configs.basic_config import Config

from morty import Experiment, ExperimentManager

from morty.cli import Option, run

from morty.trainers import TensorflowTrainingTracker

def train(

    config: Config = Option(default=Config, help="Experiment Configurations")

) -> None:

    experiment: Experiment = ExperimentManager(configs=config).create()

    (x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()

    x_train = x_train.astype("float32") / 255

    x_test = x_test.astype("float32") / 255

    x_train = np.expand_dims(x_train, -1)

    x_test = np.expand_dims(x_test, -1)

    y_train = keras.utils.to_categorical(y_train, config.num_classes)

    y_test = keras.utils.to_categorical(y_test, config.num_classes)

    model = keras.Sequential(

        [

            keras.Input(shape=config.image_shape),

            layers.Conv2D(32, kernel_size=(3, 3), activation="relu"),

            layers.MaxPooling2D(pool_size=(2, 2)),

            layers.Conv2D(64, kernel_size=(3, 3), activation="relu"),

            layers.MaxPooling2D(pool_size=(2, 2)),

            layers.Flatten(),

            layers.Dropout(0.5),

            layers.Dense(config.num_classes, activation="softmax"),

        ]

    )

    model.compile(

        loss="categorical_crossentropy",

        optimizer=config.optimizer,

        metrics=("accuracy",),

    )

    model.summary()

    training_history = model.fit(

        x_train,

        y_train,

        epochs=config.epochs,

        batch_size=config.batch_size,

        validation_split=config.val_dataset_fraction,

        callbacks=(TensorflowTrainingTracker(experiment),),

    )

    experiment.log_artifact("training_history.pkl", training_history)

    test_loss, test_accuracy = model.evaluate(x_test, y_test, verbose=0)

    print(f"Test loss: {test_loss}")

    print(f"Test accuracy: {test_accuracy}")

if __name__ == "__main__":

    run(train)

```

## Citation

If Morty helped you to streamline your research, be sure to mention it via the following BibTeX entry:

```

@Misc{Glushko2021Morty,

  author =       {Roman Glushko},

  title =        {Morty - a lightweight experiment and configuration tracking library for small ML/DL projects and Kaggling},

  howpublished = {Github},

  year =         {2021},

  url =          {https://github.com/roma-glushko/morty}

}

```

## Acknowledgment

- https://github.com/aimhubio/aim

- https://devblog.pytorchlightning.ai/introducing-lightningcli-v2-supercharge-your-training-c070d43c7dd6

- https://github.com/neptune-ai/neptune-client

- https://github.com/wandb/client/tree/master/wandb

- https://github.com/allegroai/clearml

- https://keepsake.ai/

- https://guild.ai/why-guild/

- https://metaflow.org/

- https://github.com/IDSIA/sacred

## Credentials

Made with ❤️ by Roman Glushko (c)