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Summary of ChangesHello @hjh0119, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request streamlines the Docker image build process by removing the direct installation of Ollama, likely to centralize its management or usage. It also enhances the Ubuntu-based images with Zstandard compression capabilities. A key update is the formal integration of the Highlights
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Code Review
This pull request updates dependencies and Docker build configurations. The changes are mostly straightforward, but I've found a few areas for improvement. There's some code duplication in docker/build_image.py when setting the default optimum_version, which I've commented on. I also noticed that docker/install.sh now attempts to install the optimum package twice, which should be corrected. Additionally, it appears that SwiftImageBuilder in docker/build_image.py was not updated to pass the new optimum_version argument, which could lead to inconsistencies. While I couldn't comment on that directly as it's outside the diff, it's worth looking into.
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| pip install --no-cache-dir triton auto-gptq==$autogptq_version -U && pip cache purge | ||
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| pip install --no-cache-dir optimum==$optimum_version |
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The optimum package is already being installed on line 20. This second installation is redundant and may lead to unexpected behavior if versions conflict. Please remove this line.
| RUN pip install --no-cache-dir -U funasr scikit-learn && \ | ||
| pip install --no-cache-dir -U qwen_vl_utils qwen_omni_utils librosa timm transformers accelerate peft trl safetensors && \ |
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To improve readability and reduce the number of shell commands executed in this RUN layer, you can combine these two pip install commands into one.
RUN pip install --no-cache-dir -U funasr scikit-learn qwen_vl_utils qwen_omni_utils librosa timm transformers accelerate peft trl safetensors && \
| pip install --no-cache-dir -U funasr scikit-learn && \ | ||
| pip install --no-cache-dir -U qwen_vl_utils qwen_omni_utils librosa timm transformers accelerate peft trl safetensors && \ |
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To improve readability and reduce the number of shell commands executed in this RUN layer, you can combine these two pip install commands into one.
pip install --no-cache-dir -U funasr scikit-learn qwen_vl_utils qwen_omni_utils librosa timm transformers accelerate peft trl safetensors && \
| def init_args(self, args) -> Any: | ||
| if not args.optimum_version: | ||
| args.optimum_version = '2.0.0' | ||
| return super().init_args(args) |
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This logic for setting a default optimum_version is also present in LLMImageBuilder.init_args. To avoid code duplication, consider moving this default setting to the base Builder.init_args method. This would centralize the default version management and improve maintainability.
| if not args.optimum_version: | ||
| args.optimum_version = '2.0.0' |
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This logic for setting a default optimum_version is also present in the newly added GPUImageBuilder.init_args. To avoid code duplication, consider moving this default setting to the base Builder.init_args method. This would centralize the default version management and improve maintainability.
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