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PyTorch consolidates media decoding in TorchCodec and transforms in TorchVision and TorchAudio

pytorch.org by Nicolas Hug (Meta), Scott Schneider (Meta) 4 min read Editor score 7/10

PyTorch has consolidated media processing across TorchCodec for encoding and decoding, TorchVision for image and video transforms, and TorchAudio for audio transforms. The clearer division helps teams build and maintain multimodal data pipelines.

What: TorchCodec now handles media decoding and encoding for images, video, and audio on CPU and CUDA.
How: TorchVision focuses on image and video transforms, while TorchAudio focuses on audio transforms; older I/O APIs are deprecated or removed.
Why it matters: Centralizing media I/O concentrates optimization work and dependency complexity, while giving model pipelines a single library for decoding and encoding.

TorchCodec handles decoding and encoding, while TorchVision and TorchAudio provide media transformations. Sketched from the article's own text.

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