Fix three malformed error messages - #9065
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📝 WalkthroughWalkthroughThe changes correct error message formatting in inferer and network utilities. They also separate Estimated code review effort: 1 (Trivial) | ~4 minutes Merge Risk: ⚪ Minimal · up to This PR only corrects malformed user-facing error text and adds a focused regression test. No actionable merge-blocking risk remains; the missing test docstring is a non-blocking follow-up. 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
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In `@tests/networks/utils/test_pixelunshuffle.py`:
- Around line 43-46: Add a Google-style docstring to
test_indivisible_spatial_dims describing that an indivisible spatial shape is
rejected and a ValueError is expected when pixelunshuffle is called with
scale_factor 2.
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monai/inferers/inferer.pymonai/metrics/utils.pymonai/networks/utils.pytests/networks/utils/test_pixelunshuffle.py
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Adjacent string literals concatenate in Python, and in two places the
join produces text the author clearly did not intend:
monai/networks/utils.py:443 pixelunshuffle()
"...divisible by factor 2. , spatial shape is: [7, 8]"
The second literal opens with ", " while the first already closed
with ". ", so the rendered message carries a stray ". ,".
monai/inferers/inferer.py:1776 LatentDiffusionInferer.__init__()
"...autoencoder_latent_shape must be Noneand vice versa."
No trailing space on the first literal, so two words run together.
The third is a plain typo in the same family, a missing comma in a list
of valid options, appearing in both the raised message and the docstring
that documents it:
monai/metrics/utils.py:104,144 do_metric_reduction()
'[..., "mean_channel", "sum_channel" "none"].'
Every sibling message in monai/losses/ writes this list fully
comma-separated.
All three are user-visible text only; no behaviour changes.
Signed-off-by: Hans Johnson <hans-johnson@uiowa.edu>
pixelunshuffle() raises ValueError when a spatial dimension is not divisible by the scale factor. Nothing exercised that branch: the five existing tests all use shapes that divide cleanly, so the guard clause and its message were never executed by the suite. That is why the malformed message corrected in the preceding commit survived from March 2025 without anyone noticing. This test covers that branch, and is written so it would have caught that specific defect. The wording of the assertion is load-bearing, not incidental, because the malformed code raises ValueError too: assertRaises(ValueError) alone passes on the broken message match "divisible by factor" passes on the broken message match "factor 2, spatial" fails on the broken message Only a pattern spanning the point where the two literals were joined can tell the two apart, so the assertion has to reach across it. Against the unfixed source it reports: AssertionError: "divisible by factor 2, spatial shape is: \[7, 8\]" does not match "All spatial dimensions must be divisible by factor 2. , spatial shape is: [7, 8]" The trade-off is that the test is coupled to the message text and will need updating if the message is reworded. That is the cost of pinning the defect; a looser assertion would pass either way and prove nothing. Kept as a separate commit so the text corrections can be reviewed, or reverted, independently of the new coverage. Signed-off-by: Hans Johnson <hans-johnson@uiowa.edu>
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Phase 3 recognised exactly one reviewer, greptile-apps[bot]. Any other review bot fell through is_bot() into "bot_other", a bucket the skill documents as "non-blocking, skip unless explicitly asked". On Project-MONAI/MONAI#9065 that put a genuine actionable CodeRabbit finding in the ignore pile; it was only acted on because the raw JSON was read by hand. The single GREPTILE_LOGIN constant becomes AI_REVIEW_PROVIDERS, keyed by bot login and carrying what differs per provider: how a review is requested, how one is forced for an already-reviewed head, and which in-repo file indicates the provider is configured. Findings are parsed per provider and normalised to P1/P2/P3, so CodeRabbit's Critical/Major/Minor maps onto the vocabulary the phase logic already speaks and one rule covers both. Two bugs surfaced while testing this against real PRs. The greptile parser never matched inline findings. Its pattern was alt="(P[123])"[^>]*>\s*\*\*([^*]+)\*\* but the badge is an <img> wrapped in an <a>, so a closing </a> sits between the badge and the bold title and \s* cannot span it. Most findings are inline, so Phase 3 has been running "address every P1/P2" against an empty list. InsightSoftwareConsortium/ITK#6777 reports 0 findings before this change and 2 P1s after. Provider detection read config files relative to the working directory, so triaging owner/repo#N from an unrelated checkout reported whatever that checkout happened to contain. It now queries the target repo. Unrecognised bots go to a new "bot_unknown" bucket rather than "bot_other". The two are documented differently on purpose: bot_other is ignorable, bot_unknown means nobody has classified this bot yet and it must be read before the phase can be called clean. That is the failure mode above, closed for the next review bot as well as this one. phase_3_ai_review also carries CodeRabbit's PR-level signals, merge_risk and failed_pre_merge_checks, which have no greptile equivalent and no inline comment to hang off. On Project-MONAI/MONAI#9067 merge_risk was "High" with zero inline findings — a credential-exposure issue in a workflow that would otherwise have been reported as Phase 3 clean. phase_3_greptile is retained as an alias so callers written against the old report keep working. ghtp_reply.py is untouched: replying and resolving are provider-agnostic. Verified against ITK#6714 and ITK#6777 (greptile) and MONAI#9065 and MONAI#9067 (coderabbit); test_ghtp_workstate.py still passes.
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Three error messages render as text the author clearly did not intend. Two are adjacent string literals that concatenate badly; the third is a missing comma in a list of valid options. User-visible text only — no behaviour changes.
monai/networks/utils.py:443...divisible by factor 2. , spatial shape is: [7, 8]monai/inferers/inferer.py:1776...autoencoder_latent_shape must be Noneand vice versa.monai/metrics/utils.py:104,144[..., "mean_channel", "sum_channel" "none"]Also adds a regression test for
pixelunshuffle(), whoseValueErrorpath had no coverage at all.How each one goes wrong
pixelunshuffle()— the second literal opens with", "while the first already closed with". ", so the join leaves a stray. ,:LatentDiffusionInferer.__init__()— no trailing space on the first literal, so two words run together:do_metric_reduction()— a missing comma between two entries, in both the raised message and the docstring that documents it. Every sibling message inmonai/losses/writes this list fully comma-separated, e.g.["mean", "sum", "none"].Test plan
The new test is a true regression test — against the unmodified source it fails with:
Run locally on Python 3.12 / torch 2.13.0+cu130:
tests/networks/utilstests/metricstests.inferers.test_latent_diffusion_inferertests.inferers.test_controlnet_inferers./runtests.sh --codeformatpre-commit run --all-filestests/metrics/test_compute_fid_metricerrors withsqrtm() got an unexpected keyword argument 'disp', a scipy signature change. It fails identically on unmodifieddevand is unrelated to this PR.Types of changes