{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/7"}],"enrichment":{"capability":"Provides PyTorch implementations of librosa audio feature extraction functions, enabling GPU-accelerated computation of spectrograms, mel-spectrograms, and STFT/ISTFT transforms with numerical compatibility to the original librosa.","skillfed_tags":["audio-processing","gpu-acceleration","feature-extraction"],"use_cases":["Accelerate mel-spectrogram extraction during model training by moving feature computation to GPU.","Build end-to-end differentiable audio processing pipelines where spectral features are computed on GPU.","Replace CPU-based librosa feature extraction in existing codebases with minimal code changes while gaining GPU speedup.","Implement STFT/ISTFT operations on GPU for real-time audio processing or batch inference.","Validate audio model robustness by ensuring feature extraction runs identically on CPU and GPU within numerical tolerance."],"what_it_does":"TorchLibrosa wraps common librosa audio feature extraction operations\u2014spectrogram, log-mel spectrogram, STFT, and ISTFT\u2014as modules that run on GPU. It is designed for workflows where features were previously extracted on CPU with librosa but now need GPU acceleration during training or inference. The package aims for numerical compatibility within 1e-5 of standard librosa output, so switching from librosa to TorchLibrosa should not significantly alter downstream model behavior.\n\nThe package exposes module subclasses for each operation, allowing them to be composed into feature extraction pipelines. It depends only on numpy and librosa, making installation straightforward. However, maintenance has been dormant since 2023-02-21, so bug fixes and updates to support newer versions of dependencies may not be forthcoming.","worth_installing":"Yes, if you need GPU-accelerated librosa-compatible audio features and can tolerate dormant maintenance. The low install friction and permissive license make it practical for GPU-accelerated audio feature extraction. However, verify that PyTorch is available in your environment, and be aware that no updates have shipped since 2023-02-21\u2014if you encounter bugs or incompatibilities with newer dependency versions, you may need to fork or patch locally."},"id":"torchlibrosa","links":{"html":"https://skillfed.io/packages/torchlibrosa","md":"https://skillfed.io/packages/torchlibrosa.md","pypi":"https://pypi.org/project/torchlibrosa/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2023-02-21","license_spdx":null,"license_treatment":"permissive","name":"torchlibrosa","python_support":"supports_current","summary":"PyTorch implemention of part of librosa functions."},"popularity":{"monthly_downloads":250807,"position":8617,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.1.0"}