Bump torchcodec from 0.7.0 to 0.15.0 in /apps/agent

[dependabot]

Bumps torchcodec from 0.7.0 to 0.15.0.

Release notes

Sourced from torchcodec's releases.

TorchCodec 0.15 is out! This is a small release compatible with torch >= 2.11, with the following improvements:

• meta-pytorch/torchcodec#1503 and meta-pytorch/torchcodec#1504 improved decoding coverage on some videos, where a premature "end of file" would otherwise be raised.
• meta-pytorch/torchcodec#1489 optimizes forward seeks - you should see better performance on sparse decoding scenarios, especially on CPU when num_ffmpeg_threads is high.
• Free-threaded wheels are now shipped for MacOS (and Linux, but that was already supported).

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.

... (truncated)

Commits

• dc0f10d Release 0.15 (#1505)
• 6acd419 fix bad test parametrization (#1506)
• 74c71eb Fix decoding of videos with a discarded leading keyframe (#1504)
• ae41fd5 Expose Demuxer, PacketDecoder and ColorConverter (#1501)
• d1f36b0 Fix CUDA decoder dropping frames before the first IDR (#1503)
• 727062b Update device agnostic encoding to support multiple devices (#1500)
• fb8e33d Unify Cmake and BUCK source files (#1498)
• c0106e4 Use camel_case for cpp codebase (#1492)
• eeb61c7 Optimize forward seeks (#1489)
• 8bbce65 Fix expected error message (#1490)
• Additional commits viewable in compare view

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