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Upgrade colab base image to 20260416-060047 (#1547)
Upgrade both GPU (runtime) and CPU (cpu-runtime) Colab base images to the latest available release: - GPU: `release-colab-external-images_20260416-060047_RC00` - CPU: `release-colab-external-images_20260416-060047_RC00` Previously using `release-colab-external_20260226-060109_RC00`. Note: The tag naming convention has changed from `release-colab-external_*` to `release-colab-external-images_*`. b/493600019
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Dockerfile.tmpl

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{{ if eq .Accelerator "gpu" }}
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FROM us-docker.pkg.dev/colab-images/public/runtime:release-colab-external_20260226-060109_RC00
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FROM us-docker.pkg.dev/colab-images/public/runtime:release-colab-external-images_20260416-060047_RC00
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{{ else }}
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FROM us-docker.pkg.dev/colab-images/public/cpu-runtime:release-colab-external_20260226-060109_RC00
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FROM us-docker.pkg.dev/colab-images/public/cpu-runtime:release-colab-external-images_20260416-060047_RC00
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{{ end}}
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ADD kaggle_requirements.txt /kaggle_requirements.txt
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# b/468367647: Unpin protobuf, version greater than v5.29.5 causes issues with numerous packages
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RUN uv pip install --system --force-reinstall --no-cache --no-deps torchtune
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RUN uv pip install --system --force-reinstall --no-cache "protobuf==5.29.5"
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# b/493600019: Colab base image ships numba/numba-cuda that do not support NumPy 2.4; upgrade both.
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RUN uv pip install --system --force-reinstall --no-cache numba numba-cuda
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# Adding non-package dependencies:
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ADD clean-layer.sh /tmp/clean-layer.sh

kaggle_requirements.txt

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rgf-python
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s3fs
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scikit-learn
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# Scikit-learn accelerated library for x86
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scikit-learn-intelex>=2023.0.1
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scikit-multilearn
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scikit-optimize
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scikit-plot

tests/test_sklearnex.py

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