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

Latte evaluates latent-based generative models in disentanglement learning and controllable generation with framework-agnostic, reproducible metrics.

Year
2021
Venue
arXiv 2021
Authors
3
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arxiv.org/abs/2112.10638v3ARXIV-DEFAULT
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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.

Authors

3