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Upgrade colab base image to 20260416-060047#1547

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stevemessick merged 10 commits intomainfrom
upgrade-colab-base-20260416
Apr 27, 2026
Merged

Upgrade colab base image to 20260416-060047#1547
stevemessick merged 10 commits intomainfrom
upgrade-colab-base-20260416

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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

@stevemessick stevemessick requested review from rosbo and tifftoff April 24, 2026 15:58
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LGTM assuming the jenkins build completes successfully

The old floor (>=2023.0.1) allowed uv to resolve an older version that
doesn't support NumPy 2.4 shipped in the new Colab base image. Raising
the floor to >=2025.10.1 (which has explicit NumPy 2.4 fixes) ensures
a compatible version is resolved during the main requirements install.
The version floor is now set in kaggle_requirements.txt (>=2025.10.1),
so the separate post-install step is no longer needed.
scikit-learn-intelex may not be installable with newer NumPy versions
(e.g. NumPy 2.4 from the updated Colab base image). Rather than fail
the entire test suite, skip the test gracefully when the module is
not present.
The base image's numba-cuda uses np.trapz which was removed in NumPy 2.4.
The latest numba-cuda (v0.30.0) has a fix that conditionally registers
np.trapz only for NumPy < 2.4, and uses np.trapezoid for NumPy >= 2.0.

This fixes both test_numba.test_cuda_jit and test_tsfresh (via stumpy).
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LGTM assuming the jenkins build completes successfully

It failed, a lot. Might be good to get a new review before I commit.

@stevemessick stevemessick requested review from rosbo and tifftoff April 27, 2026 17:03
Comment thread tests/test_sklearnex.py Outdated

import numpy as np

try:
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Why do we need this? Shouldn't the package always be installed given it is in kaggle_requirements.txt?

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Looking at usage of this package in kernel, we only have a handful of users using it in any given day (<5). Most days it is a either no user or a single user.

See: https://plx.corp.google.com/scripts2/python-package-usage-over-time?p=PACKAGES%3A%22sklearnex%22

We should consider simply dropping this package if this is causing installation issues. these users can always pip install it themselves.

Per reviewer feedback, scikit-learn-intelex has <5 daily users and has
been causing persistent installation issues with NumPy 2.4. Users who
need it can pip install it themselves.
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Addressed @rosbo's feedback: dropped scikit-learn-intelex from kaggle_requirements.txt and removed tests/test_sklearnex.py entirely, given the very low usage (<5 daily users). Users who need it can pip install it themselves.

@stevemessick stevemessick merged commit d6a167a into main Apr 27, 2026
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@stevemessick stevemessick deleted the upgrade-colab-base-20260416 branch April 27, 2026 18:22
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3 participants