meta-pytorch / meta-pytorch/torchcodec
Add memory consumption decoder benchmarks
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 1.2k
- Forks
- 125
- Avg merge
- 22h 47m
- Merged PRs (30d)
- 54
Description
🚀 The feature
We currently have a benchmark that's main purpose is to detect memory leaks: memprofile_decoders.py. While it does report total memory usage for TorchCodec, that's not its purpose.
What we would have, ideally, is a benchmark that meets the following purposes:
- Measures memory usage of a decoder, both resident set size and virtual size.
- Compares TorchCodec to other available open source decoders.
- Configurable to be run quickly (less than 5 seconds) for interactive debugging and longer (more than 1 minute) for more formal experiments.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with benchmarks/decoders/memprofile_decoders.py to understand the existing memory measurement and decoder setup. Determine how to compare TorchCodec with other open-source decoders and expose short and long run modes. Done means reporting resident-set and virtual memory usage for each decoder, with both interactive and formal experiment durations supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100