Comments (5)
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I would like to support parallelism at the module level: the pipeline runner inspects the execution graph and asynchronously runs modules as soon as the necessary inputs are available.
This is realizable regardless of (A) vs (B) above.
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from eta.
I agree and (A) makes it trivial to do just that. If I want to include the video preprocessing pipeline at the beginning of my new pipeline, I just reference it in the metadata file of my new pipeline and it's there.
If a pipeline developer is using (B), that means they're still writing their own pipeline/module configs manually, and that's bad. Pipeline builder should do everything!
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Related Issues (20)
- VideoReaders need to be able to seek to specific frames HOT 3
- Inconsistent success/failure when downloading models from Google drive via HTTP HOT 3
- Shorthand for exposing all module parameters as tunable
- CLI: show help anytime a command is called with no args
- `core/datasets.py` split function validation assumes 2-class setting
- core/config.py parse_number fails on 'Infinity' HOT 1
- Update ETA Dockerfile to remove nvidia-docker dependency
- Pin explicit dependency versions in ETA install
- Sample select frames problem HOT 5
- Read images from URLs HOT 1
- ETA Dockerfile does not support visualiziation
- Add support for automatically extracting models that are archives
- Upload ETA infrastructure image to GitHub CDN
- Support TensorFlow 2
- Add support for ProgressBars to `eta.core.storage`
- [Discussion] Remove `Sphinx` dependency HOT 1
- Add support for windows HOT 1
- Support annotating video-level attributes
- Progress bar regression in `v0.8.2` HOT 1
- DeprecationWarning: pkg_resources is deprecated as an API
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