coderabbitai[bot]
commented
3 months ago Walkthrough
The changes introduce multiple new files for an image captioning benchmark within a subproject. This includes configuration files, input generation functionality, and an implementation for generating captions using pre-trained models. Additionally, requirements files are added to specify necessary Python packages. The subproject reference has also been updated to a new commit in the version control system.
Changes
| File Path | Change Summary |
|---|---|
| benchmarks/700.image/701.image-captioning/config.json | New configuration file added specifying timeout, memory allocation, and programming language. |
| benchmarks/700.image/701.image-captioning/input.py | New input generation file added with functions for counting buckets and generating input configurations for images. |
| benchmarks/700.image/701.image-captioning/python/function.py | New file implements image captioning using a pre-trained model, including functions for generating captions and handling events. |
| benchmarks/700.image/701.image-captioning/python/requirements.txt | New file listing essential Python package dependencies for the image captioning project. |
| benchmarks/400.inference/421.image-captioning/config.json | New configuration file added specifying timeout, memory allocation, and programming language. |
| benchmarks/400.inference/421.image-captioning/input.py | New input generation file added with functions for counting buckets and generating input configurations for images. |
| benchmarks/400.inference/421.image-captioning/python/function.py | New file implements image captioning using a pre-trained model, including functions for generating captions and handling events. |
| benchmarks/400.inference/421.image-captioning/python/requirements.txt | New file listing essential Python package dependencies for the image captioning project. |
Poem
🐇 In the code, new changes hop,
Image captions start to bop.
With config set and input made,
Captions bloom in sunlight's shade.
Transforming bytes to words with glee,
A rabbit's joy, so wild and free! 🌼
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octonawish-akcodes
This Pull Request introduces a new
Image Caption Generation benchmarkfor SEBS, implemented using Python. This benchmark uses a hugging face modelnlpconnect/vit-gpt2-image-captioning. Link to model https://huggingface.co/nlpconnect/vit-gpt2-image-captioning and its license under Apache 2.0 https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.mdcc @mcopik
Summary by CodeRabbit
New Features
Bug Fixes