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Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models

Machine Learning 2022-03-24 v3 Artificial Intelligence Information Retrieval Mathematical Software

Abstract

Latte (for LATent Tensor Evaluation) is a Python library for evaluation of latent-based generative models in the fields of disentanglement learning and controllable generation. Latte is compatible with both PyTorch and TensorFlow/Keras, and provides both functional and modular APIs that can be easily extended to support other deep learning frameworks. Using NumPy-based and framework-agnostic implementation, Latte ensures reproducible, consistent, and deterministic metric calculations regardless of the deep learning framework of choice.

Keywords

Cite

@article{arxiv.2112.10638,
  title  = {Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models},
  author = {Karn N. Watcharasupat and Junyoung Lee and Alexander Lerch},
  journal= {arXiv preprint arXiv:2112.10638},
  year   = {2022}
}

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To appear in Software Impacts

R2 v1 2026-06-24T08:24:48.584Z