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chore(release): prepare 1.0.0 metadata and changelog#47

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melvinbarbaux merged 1 commit intomainfrom
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Mar 10, 2026
Merged

chore(release): prepare 1.0.0 metadata and changelog#47
melvinbarbaux merged 1 commit intomainfrom
release

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Summary

What does this PR change?

Checklist

  • Tests added or updated
  • CI green
  • Changelog updated
  • Documentation updated

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Anything reviewers should know?

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codecov bot commented Mar 10, 2026

Codecov Report

✅ All modified and coverable lines are covered by tests.

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💡 Codex Review

if isinstance(X, np.ndarray) and X.ndim >= 3:
samples = [X[i] for i in range(X.shape[0])] if X.ndim == 4 else [X]

P1 Badge Handle 3D grayscale arrays as batched inputs

Treating np.ndarray inputs as batched data only when ndim == 4 makes (N, H, W) vision tensors fail in encode. With common grayscale datasets (for example, MNIST-style arrays loaded as (N, H, W)), this path keeps the entire batch as one sample (samples = [X]), and _to_nchw then cannot infer channels for shape (N, H, W) and raises a validation error; in edge cases it can also misinterpret sample count. This breaks torchvision:resnet18 preprocessing unless callers manually reshape to 4D beforehand.

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@melvinbarbaux melvinbarbaux merged commit f13e62e into main Mar 10, 2026
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@melvinbarbaux melvinbarbaux deleted the release branch March 10, 2026 15:28
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