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.
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
- Hosting
- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/2112.10638v3ARXIV-DEFAULT
- TL;DR
- Semantic Scholar