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Bump torchcodec from 0.7.0 to 0.14.0 in /apps/agent - #6

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Bump torchcodec from 0.7.0 to 0.14.0 in /apps/agent#6
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Bumps torchcodec from 0.7.0 to 0.14.0.

Release notes

Sourced from torchcodec's releases.

TorchCodec 0.14: HDR Video Decoding for CPU & CUDA, and Fast Wav Decoder

TorchCodec 0.14 is out! It is compatible with torch >= 2.11. It comes with two major additions: a fast audio WavDecoder, and support for HDR video decoding!

Fast wav decoder

Inspired by SDPL's fast wav decoder, TorchCodec now has a dedicated WavDecoder for decoding WAV files. It bypasses FFmpeg entirely and reads WAV data directly, resulting in significantly faster decoding. It supports multiple sample formats (int16, int32, float32, etc.), and can decode from files, bytes, or file-like objects.

from torchcodec.decoders import WavDecoder
decoder = WavDecoder("audio.wav")
samples = decoder.get_all_samples()  # AudioSamples with data and sample_rate

Read more in our docs.

HDR Video Decoding

VideoDecoder now supports HDR (High Dynamic Range) video decoding without losing precision. When output_dtype=torch.float32 is specified, the decoder outputs RGB float32 frames in [0, 1], preserving the full HDR color range. This is supported for both CPU and CUDA!

import torch
from torchcodec.decoders import VideoDecoder
decoder = VideoDecoder("hdr_video.mp4", output_dtype=torch.float32)
frame = decoder[0]  # Full HDR precision in float32

Read more in our docs.

⚠️ This feature is in beta stage, so behavior may slightly change depending on user feedback. Let us know if you encounter any issue!

Other Improvements

  • Improved audio seeking: AudioDecoder seeking is now much faster (#1449)
  • Dropped NPP dependency: TorchCodec no longer depends on NVIDIA's NPP library, which will simplify installing and using TorchCodec for CUDA decoding.

Bug Fixes

  • Fix a rare crash scenario during process teardown with the CUDA decoder (#1441)
  • Fix CUDA decoding of videos with odd dimensions(#1462)

TorchCodec 0.13

TorchCodec 0.13 is out! It is compatible with torch >= 2.11, and it is packed with new features.

Multi-stream iterative Encoder

This release comes with a new major feature: the multi-stream Encoder! The Encoder supports multiple streams and incremental encoding. Frames and samples can be added progressively, which is useful when data is generated on-the-fly or when encoding both audio and video into the same container.

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Bumps [torchcodec](https://github.com/pytorch/torchcodec) from 0.7.0 to 0.14.0.
- [Release notes](https://github.com/pytorch/torchcodec/releases)
- [Commits](meta-pytorch/torchcodec@v0.7.0...v0.14.0)

---
updated-dependencies:
- dependency-name: torchcodec
  dependency-version: 0.14.0
  dependency-type: direct:development
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Jul 4, 2026
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dependabot Bot commented on behalf of github Jul 17, 2026

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Superseded by #20.

@dependabot dependabot Bot closed this Jul 17, 2026
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dependabot Bot deleted the dependabot/pip/apps/agent/torchcodec-0.14.0 branch July 17, 2026 00:54
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