LAION-AI / LAION-AI/CLIP_benchmark
Zeroshot-classification accuracy function dimensionality bug
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- Dominant language
- Python
- Stars
- 815
- Forks
- 102
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Description
I was using the zeroshot_classification.py accuracy function to calculate top 1 and top 5 accuracy. I passed two tensors as required: output with shape [50000, 1000] and target with shape [50000] to it, and got a TypeError: only 0-dimensional arrays can be converted to Python scalars error from the accuracy function. I fixed it by adding a squeeze function to the result computation.
Unsure if this is a bug or if there is a different intended way of using it. Can open a PR if this is a bug.
Contributor guide
First steps
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- Open a pull request that references the issue number.
Research direction
Start in zeroshot_classification.py and inspect the accuracy function's result computation with output shaped [50000, 1000] and target shaped [50000]. Reproduce the reported TypeError for top-1 and top-5 accuracy, then verify that the function accepts these tensor shapes and returns the expected accuracy values without the dimensionality error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100