में बचाया:
| मुख्य लेखकों: | , , , , , , |
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| स्वरूप: | Preprint |
| प्रकाशित: |
2024
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| विषय: | |
| ऑनलाइन पहुंच: | https://arxiv.org/abs/2408.03204 |
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| _version_ | 1866917742284636160 |
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| author | Lee, Sungho Martínez-Ramírez, Marco Liao, Wei-Hsiang Uhlich, Stefan Fabbro, Giorgio Lee, Kyogu Mitsufuji, Yuki |
| author_facet | Lee, Sungho Martínez-Ramírez, Marco Liao, Wei-Hsiang Uhlich, Stefan Fabbro, Giorgio Lee, Kyogu Mitsufuji, Yuki |
| contents | We present GRAFX, an open-source library designed for handling audio processing graphs in PyTorch. Along with various library functionalities, we describe technical details on the efficient parallel computation of input graphs, signals, and processor parameters in GPU. Then, we show its example use under a music mixing scenario, where parameters of every differentiable processor in a large graph are optimized via gradient descent. The code is available at https://github.com/sh-lee97/grafx. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_03204 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch Lee, Sungho Martínez-Ramírez, Marco Liao, Wei-Hsiang Uhlich, Stefan Fabbro, Giorgio Lee, Kyogu Mitsufuji, Yuki Sound Audio and Speech Processing We present GRAFX, an open-source library designed for handling audio processing graphs in PyTorch. Along with various library functionalities, we describe technical details on the efficient parallel computation of input graphs, signals, and processor parameters in GPU. Then, we show its example use under a music mixing scenario, where parameters of every differentiable processor in a large graph are optimized via gradient descent. The code is available at https://github.com/sh-lee97/grafx. |
| title | GRAFX: An Open-Source Library for Audio Processing Graphs in PyTorch |
| topic | Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2408.03204 |