Alquitable is a Python package that provides a Keras-based set of tools to enhance Alquimodelia.
It provides the loss function and callbacks to apply to keras models
To use Alquitable, follow these steps:
pip install alquitableSince Aquitable is based on keras-core you can choose which backend to use, otherwise it will default to tensorflow.
To change backend change the KERAS-BACKEND enviromental variable. Follow this.
To get an arquiteture you only need to have a simple configuration and call the module:
# Previous code and imports
...
from alquitable import losses, callbacks
# Based on forecat StackedCNN
loss_funtion=losses.weighted_loss
callback = callbacks.StopOnNanLoss
StackedCNN.compile(loss=loss_funtion)
StackedCNN.fit(
...
callbacks=callback
)
Contributions to Alquitable are welcome! If you find any issues or have suggestions for improvement, please feel free to contribute. Make sure to update tests as appropriate and follow the contribution guidelines.
Alquitable is licensed under the MIT License, which allows you to use, modify, and distribute the package according to the terms of the license. For more details, please refer to the LICENSE file.