NO-JIRA: tests(fix): remove unused tensorboard import (fixes #2077) #2111
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WalkthroughEdited the test notebook Changes
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes Assessment against linked issues
Pre-merge checks and finishing touches❌ Failed checks (2 warnings)
✅ Passed checks (3 passed)
✨ Finishing touches🧪 Generate unit tests
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Hi @pramodtoraskar. Thanks for your PR. I'm waiting for a opendatahub-io member to verify that this patch is reasonable to test. If it is, they should reply with Once the patch is verified, the new status will be reflected by the I understand the commands that are listed here. Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes-sigs/prow repository. |
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Hello Team, I’m a new contributor and still learning the review process. Thanks for clarifying the next steps. I’ll wait for an @paulovmr — when you have a chance, could you please review and, if everything looks good, apply Please let me know if there’s anything else I should provide to support the review. Thank you! |
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/assign @paulovmr |
jiridanek
reviewed
Aug 26, 2025
| "import json\n", | ||
| "import re\n", | ||
| "import unittest\n", | ||
| "import tensorflow as tf\n", |
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Suggested change
| "import tensorflow as tf\n", | |
| "import tensorflow as tf\n", | |
| "import tensorboard as _ # for testing purposes\n", |
When reporting the github issue, I was not sure if the import is genuinely unused or whether simply importing it is valuable as a sort of test. It checks that tensorboard is installed and is importable.
Maybe we should have a dedicated test that imports tensorboard to make it explicit.
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Thank you @jiridanek for the thoughtful suggestion! I appreciate you taking the time to review this thoroughly.
I have a few thoughts I'd like to discuss, as a first-time contributor learning the best practices:
Question about the approach:
- The original issue was a simple F401 linting warning (unused import)
- Your suggestion adds both an import AND a dedicated test method
- I'm wondering if this might be over-engineering for the problem we're solving
Alternative approaches to consider:
- Remove import entirely - simplest, cleanest solution
- Use import in existing test - import where it's actually needed
- Your suggested approach - explicit import + dedicated test
Questions for the team:
- Is tensorboard actually a required dependency, or was this import leftover code?
- Do we need both the import validation AND the existing
test_tensorboard()method? - What's the project's philosophy on handling linting warnings vs. adding explicit tests?
As a newcomer, I'd love to understand the reasoning behind the preferred approach. I'm happy to implement whatever the team thinks is best - I'm just trying to understand the trade-offs and learn the project's standards.
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Another thing. I did not check, but I imagine the import tensorboard line may be duplicated many times in the repo, and many times it will be an unused import. So the fix should address all the places.
@coderabbitai can you please help find the tensorboard imports in this repo and determine if they are used or unused?
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🧩 Analysis chain
@jiridanek I'll help you find all tensorboard imports in the repository and analyze their usage patterns.
🏁 Script executed:
#!/bin/bash
# Find all files containing tensorboard imports
echo "=== Finding all tensorboard import statements ==="
rg -n "import tensorboard" --type=py --type=ipynb
echo -e "\n=== Finding alternative tensorboard import patterns ==="
rg -n "from tensorboard" --type=py --type=ipynb
echo -e "\n=== Finding files that reference tensorboard after import ==="
rg -n "tensorboard\." --type=py --type=ipynb
echo -e "\n=== Checking for tf.keras.callbacks.TensorBoard usage ==="
rg -n "tf\.keras\.callbacks\.TensorBoard" --type=py --type=ipynb
echo -e "\n=== Checking for TensorBoard callback usage ==="
rg -n "TensorBoard" --type=py --type=ipynb
Length of output: 1025
🏁 Script executed:
#!/bin/bash
# Find all files containing tensorboard imports - corrected approach
echo "=== Finding all tensorboard import statements in Python files ==="
rg -n "import tensorboard" --type=py
echo -e "\n=== Finding all tensorboard import statements in Jupyter notebooks ==="
rg -n "import tensorboard" --glob "*.ipynb"
echo -e "\n=== Finding alternative tensorboard import patterns in Python files ==="
rg -n "from tensorboard" --type=py
echo -e "\n=== Finding alternative tensorboard import patterns in Jupyter notebooks ==="
rg -n "from tensorboard" --glob "*.ipynb"
echo -e "\n=== Finding files that reference tensorboard after import in Python files ==="
rg -n "tensorboard\." --type=py
echo -e "\n=== Finding files that reference tensorboard after import in Jupyter notebooks ==="
rg -n "tensorboard\." --glob "*.ipynb"
echo -e "\n=== Checking for tf.keras.callbacks.TensorBoard usage ==="
rg -n "tf\.keras\.callbacks\.TensorBoard" --type=py --glob "*.ipynb"
echo -e "\n=== Checking for TensorBoard callback usage ==="
rg -n "TensorBoard" --type=py --glob "*.ipynb"
Length of output: 5077
@jiridanek Excellent intuition! Your suspicion was correct. I found exactly 3 files with unused import tensorboard statements:
Files with unused tensorboard imports:
jupyter/rocm/tensorflow/ubi9-python-3.11/test/test_notebook.ipynb:15jupyter/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:15jupyter/tensorflow/ubi9-python-3.11/test/test_notebook.ipynb:15
Analysis:
- All imports are genuinely unused: No files use
tensorboard.anywhere - TensorBoard functionality is present: All files use
tf.keras.callbacks.TensorBoard()instead - Same pattern everywhere: All 3 files have identical unused imports on line 15
Current situation:
- The current PR (NO-JIRA: tests(fix): remove unused tensorboard import (fixes #2077) #2111) only addresses the ROCm Python 3.12 file
- Two more files need the same fix
Recommendation:
Rather than having separate PRs for each file, I recommend expanding this PR to address all 3 instances comprehensively. This would:
- Fix the root cause completely - no partial solutions
- Follow DRY principle - one fix for one recurring issue
- Reduce review overhead - single comprehensive review vs multiple small ones
- Ensure consistency - all TensorFlow test notebooks follow the same pattern
Would you like me to help create a GitHub issue to track the comprehensive fix for all remaining files? Based on the established patterns in your repository, this seems like the systematic approach that would best serve the project.
🧠 Learnings used
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-06T15:51:55.727Z
Learning: jiridanek requested GitHub issue creation for unused pathlib.Path import in jupyter/minimal/ubi9-python-3.12/test/test_notebook.ipynb during PR #1686 review. Issue #1687 was created with comprehensive problem description covering unused import at line 14, clear solution with diff example, detailed acceptance criteria including verification steps and broader audit suggestion, and proper context linking with PR and comment references, assigned to dibryant, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-06T15:51:58.704Z
Learning: jiridanek requested GitHub issue creation for unused pathlib.Path import removal in jupyter/minimal/ubi9-python-3.12/test/test_notebook.ipynb during PR #1686 review. Issue #1688 was successfully created with comprehensive problem description covering static analysis findings, specific file location and line number, clear before/after solution, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1340 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, testing approach, and implementation timeline, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1345 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, and testing approach, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1591
File: codeserver/ubi9-python-3.11/Pipfile.lock:1-1
Timestamp: 2025-08-01T16:03:18.732Z
Learning: jiridanek requested GitHub issue creation for Keras 3 / TensorFlow API compatibility problem during PR #1591 review. Issue #1594 was successfully created with comprehensive problem description covering API confusion between standalone keras==3.11.1 and tf.keras bundled with tensorflow==2.18.1, multiple solution options (remove standalone Keras, set KERAS_BACKEND, or documentation), clear acceptance criteria, affected files analysis, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:71-76
Timestamp: 2025-07-04T06:04:43.085Z
Learning: jiridanek requested GitHub issue creation for duplicate CSV loading and validation problem in jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb during PR #1306 review. Issue #1322 was created with comprehensive problem description covering code redundancy, runtime failure risks, network inefficiency, and test reliability concerns, along with detailed solution including duplicate line removal, data validation implementation, repository-wide audit, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2000
File: runtimes/rocm-pytorch/ubi9-python-3.11/requirements.txt:807-809
Timestamp: 2025-08-20T12:39:54.827Z
Learning: Issue #2055 tracks the remaining runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt file that stayed at jupyter-core==5.7.2 during PR #2000, which will be addressed separately due to specific challenges with that ROCm TensorFlow image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2000
File: runtimes/tensorflow/ubi9-python-3.11/Pipfile:41-41
Timestamp: 2025-08-20T12:19:34.523Z
Learning: jiridanek created GitHub issue #2055 to track the remaining runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile.lock file that stayed at jupyter-core==5.7.2 during PR #2000, ensuring systematic follow-up for complete CVE-2025-30167 remediation across all runtime images in the opendatahub-io/notebooks repository.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
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TensorBoard functionality is present: All files use tf.keras.callbacks.TensorBoard() instead
Important to know, so the import by itself is not the only thing in the test that ensures TensorBoard is present in the image.
We will be removing the 3.11 code soon-ish, so we don't need to worry about those files
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Seems like the humans are having a chat. I'll hop back into my burrow for now. If you need me again, just tag @coderabbitai in a new comment, and I'll come hopping out!
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It would've been nice if the test actually asserted something about the tensorboard.
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@jiridanek Thank you for the detailed analysis! you're absolutely right - I think I should fix all 3 files in one PR rather than just one.
Quick Questions:
- Should I expand this PR to fix all 3 unused tensorboard imports?
- For the test improvements you mentioned - should I add actual assertions that validate TensorBoard functionality works?
- Since 3.11 code is being removed soon - should I still fix those files or focus only on the 3.12 ones?
I'm happy to make this PR comprehensive and address all instances. Just want to make sure I'm following the right approach.
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Hello @jiridanek @atheo89,
Looking for you comment to complete this PR. Any thoughts?
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Hello Team
Looking for you comment to complete & merge this PR.
cc: @jiridanek @atheo89
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/cc @atheo89 wdyt? |
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/lgtm given the comments above, I think this can go in as it is, but I'll want until tomorrow so andriana can also comment |
jiridanek
changed the title
jiridanek
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@jiridanek @atheo89 - I see the CI is failing due to missing This seems unrelated to my tensorboard import changes. Should I:
The test failures are preventing the build from completing. |
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@pramodtoraskar this is known issue, it has been failing for a long time already and related ones
It is entirely unrelated to your changes. If you want, you can sure take it and see if you can fix RHOAIENG-19036 and maybe do some of the improvements around, if you think of something. With the removal of 3.11 workbenches in maybe the problem went away? But I would not bet on it. Probably the wrong code just got copypasted to 3.12 version of the workbench. |
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@jiridanek - I appreciate the suggestion to also look into RHOAIENG-19036, but at this time I’d prefer to keep this PR focused only on the TensorBoard import fix. Since this is my first contribution, my goal is to master the basics and get a clean, simple fix merged. I’d be happy to revisit those areas in future contributions once I’m more familiar with the codebase. |
@pramodtoraskar I thought you're asking about further work. This PR is ready for merge, IMO. |
…ixes opendatahub-io#2077) - Remove unused 'import tensorboard' from test_notebook.ipynb - Fixes Ruff F401 error: unused import - TensorBoard functionality still works via tf.keras.callbacks.TensorBoard Signed-off-by: Pramod Toraskar <[email protected]>
…t_notebook.ipynb All checks passed!
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Actionable comments posted: 0
🧹 Nitpick comments (3)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (3)
71-71: Use unittest assertions instead of bare assert.Bare asserts can be optimized out; prefer unittest helpers.
- assert predictions + self.assertIsNotNone(predictions) + self.assertGreater(getattr(predictions, "size", 0), 0, "No predictions produced")
85-87: Fix tensorboard import check; remove unused noqa.Ruff flags the
# noqa: PLC0415, F401as unused (RUF100). Also avoid an unused import by probing via importlib.- # Check tensorboard is installed - import tensorboard as _ # noqa: PLC0415, F401 + # Check tensorboard is installed + import importlib + try: + importlib.import_module("tensorboard") + except ModuleNotFoundError as e: + self.fail(f"tensorboard not installed or import failed: {e}")
99-99: Avoid leaving ./logs behind; write to a temp dir.Prevents repo pollution on repeated runs.
- log_dir = "./logs" + import tempfile + log_dir = tempfile.mkdtemp(prefix="tb-")
📜 Review details
Configuration used: Path: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (1)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb(2 hunks)
🧰 Additional context used
🧠 Learnings (26)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-09-16T15:46:55.327Z
Learning: jiridanek requested GitHub issue creation for TensorFlow test notebook improvements during PR #1975 review, consolidating multiple review nitpicks into a single comprehensive issue covering code organization, error handling, documentation consistency, testing methodology, and notebook standards alignment. Issue #2491 was successfully created with detailed problem descriptions, three solution options, comprehensive acceptance criteria, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-06T15:51:58.704Z
Learning: jiridanek requested GitHub issue creation for unused pathlib.Path import removal in jupyter/minimal/ubi9-python-3.12/test/test_notebook.ipynb during PR #1686 review. Issue #1688 was successfully created with comprehensive problem description covering static analysis findings, specific file location and line number, clear before/after solution, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-09-16T15:46:55.327Z
Learning: jiridanek requested GitHub issue creation for TensorFlow test notebook improvements during PR #1975 review, consolidating multiple review nitpicks into a single comprehensive issue covering code organization, error handling, documentation consistency, testing methodology, and notebook standards alignment, following the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2265
File: .tekton/odh-workbench-jupyter-tensorflow-rocm-py312-ubi9-pull-request.yaml:16-17
Timestamp: 2025-09-05T12:10:24.058Z
Learning: jiridanek requested GitHub issue creation for unrelated datascience repo path watches in ROCm TensorFlow pull request pipeline during PR #2265 review, specifically to remove unnecessary mongodb-org-6.0.repo-x86_64 and mssql-2022.repo-x86_64 path watches that are not actually used by the ROCm TensorFlow Dockerfile while preserving setup-elyra.sh and other relevant dependencies, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-06T15:51:55.727Z
Learning: jiridanek requested GitHub issue creation for unused pathlib.Path import in jupyter/minimal/ubi9-python-3.12/test/test_notebook.ipynb during PR #1686 review. Issue #1687 was created with comprehensive problem description covering unused import at line 14, clear solution with diff example, detailed acceptance criteria including verification steps and broader audit suggestion, and proper context linking with PR and comment references, assigned to dibryant, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-01T14:46:03.215Z
Learning: jiridanek requested GitHub issue creation for two nitpicks during PR #1588 review: comment wording improvement in ROCm TensorFlow Dockerfile and typo fix in Jupyter DataScience Dockerfile stage header. Issues #1589 and #1590 were successfully created with comprehensive problem descriptions, specific file locations and line numbers, clear before/after solutions, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-27T15:14:05.619Z
Learning: jiridanek requested GitHub issue creation for tensorflow-rocm dependency-metadata override reassessment during PR #2145 review, identifying that the current `requires-dist = []` approach may be dangerous and hard to maintain since environments already exclude Windows. Issue #2153 was created with comprehensive safety analysis covering metadata masking risks, maintenance concerns, investigation areas for necessity testing, multiple solution options from complete removal to targeted alternatives, and acceptance criteria for proper dependency management, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-27T19:00:57.755Z
Learning: jiridanek requested GitHub issue creation for tensorflow[and-cuda] extra removal investigation during PR #2145 review, addressing the concern that this extra forces CUDA-specific wheels causing cross-platform conflicts while Docker images already supply CUDA via base layer. Issue #2168 was created with comprehensive investigation framework covering dependency differences, runtime verification, performance testing, cross-platform compatibility, and clear acceptance criteria for deciding whether to remove the extra in favor of base tensorflow package.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-09-12T09:51:55.421Z
Learning: TensorFlow ROCm Python 3.12 support is FULLY implemented in opendatahub-io/notebooks repository with complete source directories: runtimes/rocm-tensorflow/ubi9-python-3.12/ contains Dockerfile.rocm, pyproject.toml, and pylock.toml; jupyter/rocm/tensorflow/ubi9-python-3.12/ contains full workbench structure with kustomize and test directories. Both odh-workbench-jupyter-tensorflow-rocm-py312-ubi9 and odh-pipeline-runtime-tensorflow-rocm-py312-ubi9 entries in params-latest.env are legitimate and properly supported, contradicting earlier assumptions about missing Python 3.12 ROCm TensorFlow support.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-09-12T09:51:55.421Z
Learning: During PR #2103 review investigation, found that runtimes/rocm-tensorflow/ubi9-python-3.12/ directory DOES exist in the repository, correcting initial assessment that all TensorFlow ROCm Python 3.12 entries in params-latest.env were orphaned. The pipeline runtime component appears to have proper source directory support.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-06-16T11:32:09.203Z
Learning: In the opendatahub-io/notebooks repository, there is a known issue with missing `runtimes/rocm/pytorch/ubi9-python-3.11/kustomize/base/kustomization.yaml` file that causes rocm runtime tests to fail with "no such file or directory" error. This is tracked in JIRA RHOAIENG-22044 and was intended to be fixed in PR #1015.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-23T16:18:42.922Z
Learning: The TensorFlow ROCm Python 3.12 compatibility issue in opendatahub-io/notebooks PR #1259 was caused by using tensorflow-rocm==2.14.0.600 in Pipfile.lock which lacks Python 3.12 wheels, while the Pipfile specifies tensorflow_rocm=~=2.18.1. The solution requires updating Pipfile sources to include https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/ repository which contains tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl and regenerating Pipfile.lock using the piplock-refresh GitHub Action.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2000
File: runtimes/rocm-pytorch/ubi9-python-3.11/requirements.txt:807-809
Timestamp: 2025-08-20T12:39:54.827Z
Learning: Issue #2055 tracks the remaining runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt file that stayed at jupyter-core==5.7.2 during PR #2000, which will be addressed separately due to specific challenges with that ROCm TensorFlow image.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2000
File: runtimes/pytorch/ubi9-python-3.12/requirements.txt:804-807
Timestamp: 2025-08-20T12:18:19.213Z
Learning: The runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt file remained at jupyter-core==5.7.2 while other runtime images were updated to 5.8.1 during PR #2000 to address CVE-2025-30167. jiridanek requested a separate GitHub issue to track this remaining update as the reason for the file being stuck at the old version was unclear.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2000
File: runtimes/pytorch/ubi9-python-3.12/requirements.txt:804-807
Timestamp: 2025-08-20T12:18:19.213Z
Learning: The runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt file remained at jupyter-core==5.7.2 while other runtime images were updated to 5.8.1 during PR #2000 to address CVE-2025-30167. jiridanek requested a separate GitHub issue (#2055) to track this remaining update as the reason for the file being stuck at the old version was unclear.
📚 Learning: 2025-07-02T18:59:15.788Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-09-16T15:46:55.327Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-09-16T15:46:55.327Z
Learning: jiridanek requested GitHub issue creation for TensorFlow test notebook improvements during PR #1975 review, consolidating multiple review nitpicks into a single comprehensive issue covering code organization, error handling, documentation consistency, testing methodology, and notebook standards alignment, following the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-06T15:51:55.727Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-06T15:51:55.727Z
Learning: jiridanek requested GitHub issue creation for unused pathlib.Path import in jupyter/minimal/ubi9-python-3.12/test/test_notebook.ipynb during PR #1686 review. Issue #1687 was created with comprehensive problem description covering unused import at line 14, clear solution with diff example, detailed acceptance criteria including verification steps and broader audit suggestion, and proper context linking with PR and comment references, assigned to dibryant, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-06T15:51:58.704Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-06T15:51:58.704Z
Learning: jiridanek requested GitHub issue creation for unused pathlib.Path import removal in jupyter/minimal/ubi9-python-3.12/test/test_notebook.ipynb during PR #1686 review. Issue #1688 was successfully created with comprehensive problem description covering static analysis findings, specific file location and line number, clear before/after solution, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-09-16T15:46:55.327Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-09-16T15:46:55.327Z
Learning: jiridanek requested GitHub issue creation for TensorFlow test notebook improvements during PR #1975 review, consolidating multiple review nitpicks into a single comprehensive issue covering code organization, error handling, documentation consistency, testing methodology, and notebook standards alignment. Issue #2491 was successfully created with detailed problem descriptions, three solution options, comprehensive acceptance criteria, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-20T12:39:54.827Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2000
File: runtimes/rocm-pytorch/ubi9-python-3.11/requirements.txt:807-809
Timestamp: 2025-08-20T12:39:54.827Z
Learning: Issue #2055 tracks the remaining runtimes/rocm-tensorflow/ubi9-python-3.12/requirements.txt file that stayed at jupyter-core==5.7.2 during PR #2000, which will be addressed separately due to specific challenges with that ROCm TensorFlow image.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-09T08:07:24.937Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-09T08:07:24.937Z
Learning: jiridanek requested GitHub issue creation for tensorflow_rocm Python 3.12 compatibility problem during PR #1333 review. Issue #1354 was successfully created with comprehensive problem description covering missing cp312 wheels causing build failures, three solution options (upstream TensorFlow, Python 3.11 only, custom build), clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-08T19:29:32.006Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1340 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, testing approach, and implementation timeline, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-08T19:29:32.006Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-08T19:29:32.006Z
Learning: jiridanek requested GitHub issue creation for investigating TensorFlow "and-cuda" extras usage patterns during PR #1333 review. Issue #1345 was created with comprehensive investigation framework covering platform-specific analysis, deployment scenarios, TensorFlow version compatibility, clear acceptance criteria, and testing approach, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-08T13:21:09.150Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:112-126
Timestamp: 2025-07-08T13:21:09.150Z
Learning: jiridanek requested GitHub issue creation for notebook linting and formatting improvements during PR #1306 review, specifically to address inconsistent metadata across .ipynb files and implement systematic quality standards. This continues the established pattern of comprehensive issue creation for code quality improvements with detailed problem descriptions, multiple solution options, phased acceptance criteria, and proper context linking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-01T16:03:18.732Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1591
File: codeserver/ubi9-python-3.11/Pipfile.lock:1-1
Timestamp: 2025-08-01T16:03:18.732Z
Learning: jiridanek requested GitHub issue creation for Keras 3 / TensorFlow API compatibility problem during PR #1591 review. Issue #1594 was successfully created with comprehensive problem description covering API confusion between standalone keras==3.11.1 and tf.keras bundled with tensorflow==2.18.1, multiple solution options (remove standalone Keras, set KERAS_BACKEND, or documentation), clear acceptance criteria, affected files analysis, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-27T15:14:05.619Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-27T15:14:05.619Z
Learning: jiridanek requested GitHub issue creation for tensorflow-rocm dependency-metadata override reassessment during PR #2145 review, identifying that the current `requires-dist = []` approach may be dangerous and hard to maintain since environments already exclude Windows. Issue #2153 was created with comprehensive safety analysis covering metadata masking risks, maintenance concerns, investigation areas for necessity testing, multiple solution options from complete removal to targeted alternatives, and acceptance criteria for proper dependency management, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-08T19:35:49.482Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-09-05T12:10:24.058Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2265
File: .tekton/odh-workbench-jupyter-tensorflow-rocm-py312-ubi9-pull-request.yaml:16-17
Timestamp: 2025-09-05T12:10:24.058Z
Learning: jiridanek requested GitHub issue creation for unrelated datascience repo path watches in ROCm TensorFlow pull request pipeline during PR #2265 review, specifically to remove unnecessary mongodb-org-6.0.repo-x86_64 and mssql-2022.repo-x86_64 path watches that are not actually used by the ROCm TensorFlow Dockerfile while preserving setup-elyra.sh and other relevant dependencies, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-20T17:51:39.525Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:31-36
Timestamp: 2025-08-20T17:51:39.525Z
Learning: jiridanek consistently escalates point issues identified during PR reviews into systematic repository-wide improvements. When CodeRabbit flagged missing libxcrypt-compat in a single ROCm TensorFlow Python 3.12 image during PR #1259 review, jiridanek requested creation of issue #2075 for systematic review and fixing of all Python 3.12 UBI9 images, demonstrating his comprehensive approach to infrastructure consistency and code quality.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-11T11:15:47.424Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-08T19:09:48.746Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-08T19:09:48.746Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-20T12:19:34.523Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2000
File: runtimes/tensorflow/ubi9-python-3.11/Pipfile:41-41
Timestamp: 2025-08-20T12:19:34.523Z
Learning: jiridanek created GitHub issue #2055 to track the remaining runtimes/rocm-tensorflow/ubi9-python-3.12/Pipfile.lock file that stayed at jupyter-core==5.7.2 during PR #2000, ensuring systematic follow-up for complete CVE-2025-30167 remediation across all runtime images in the opendatahub-io/notebooks repository.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-01T14:46:03.215Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-01T14:46:03.215Z
Learning: jiridanek requested GitHub issue creation for two nitpicks during PR #1588 review: comment wording improvement in ROCm TensorFlow Dockerfile and typo fix in Jupyter DataScience Dockerfile stage header. Issues #1589 and #1590 were successfully created with comprehensive problem descriptions, specific file locations and line numbers, clear before/after solutions, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-03T07:03:45.020Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-07-03T16:18:59.234Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue. The pattern is actively managed through issues like #1243 "Improve error handling in get_expected_version() functions across test notebooks" and #1254 "Fix undefined variable error in ROCm PyTorch Python 3.12 test notebook".
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-08T08:38:32.988Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1760
File: jupyter/pytorch+llmcompressor/ubi9-python-3.11/Dockerfile.cuda:241-244
Timestamp: 2025-08-08T08:38:32.988Z
Learning: Policy: In opendatahub-io/notebooks, do not remove micropipenv from Python 3.11 images to avoid breaking existing users. Cleanups can deduplicate duplicate installs and remove unused uv, but micropipenv must remain present in 3.11 images.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-27T07:37:13.713Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#2114
File: Makefile:22-24
Timestamp: 2025-08-27T07:37:13.713Z
Learning: jiridanek's approach to removing Python 3.11 workbenches involves handling different components incrementally across multiple PRs: Tekton pipeline cleanup in the current PR, pr-merge-image-delete.yml cleanup in a subsequent PR, while preserving historical context comments in workflow templates that don't require changes.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
📚 Learning: 2025-08-05T17:24:08.616Z
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-05T17:24:08.616Z
Learning: jiridanek requested PR review for #1521 covering s390x architecture support improvements, demonstrating continued focus on systematic multi-architecture compatibility enhancements in the opendatahub-io/notebooks repository through clean implementation with centralized configuration, proper CI integration, and architecture-aware testing patterns.
Applied to files:
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
🪛 Ruff (0.12.2)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb
78-78: Unused noqa directive (non-enabled: PLC0415, F401)
Remove unused noqa directive
(RUF100)
🔇 Additional comments (1)
jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb (1)
13-15: LGTM on non-functional tidy-ups.Import tweaks, quoting/style changes, and minor whitespace look good.
Also applies to: 21-22, 25-31, 37-37, 41-41, 43-45, 48-50, 56-56, 66-66, 75-75, 77-77, 90-90, 94-94, 99-99, 104-104
|
/ok-to-test |
jiridanek
approved these changes
Sep 16, 2025
|
[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: jiridanek The full list of commands accepted by this bot can be found here. The pull request process is described here
Needs approval from an approver in each of these files:
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@coderabbitai suggest next steps |
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Tip For best results, initiate chat on the files or code changes. 🧩 Analysis chain@jiridanek Based on the PR status and conversation, here are the suggested next steps: Immediate Next Steps
Follow-up Opportunities
RecommendationMerge this PR now - it successfully addresses issue #2077 with a clean, focused fix. The CI failures shouldn't block this straightforward improvement. The systematic approach shown here (focused PR scope, clear issue resolution) aligns well with the established patterns for code quality improvements in this repository. 🏁 Script executed: Length of output: 43178 @jiridanek Based on the current PR status, here are the next steps: Current Status
Immediate Issues to Address
Recommended Next StepsOption A - Quick Fix (Preferred):
Option B - Comprehensive Approach:
My RecommendationFix the RUF100 error now to unblock this PR, then merge it. The core tensorboard import removal is sound and addresses issue #2077 successfully. The other nitpicks can be addressed systematically later if desired. Would you like me to create a follow-up issue for the broader test improvements, following your established pattern? 🧠 Learnings used |
|
@pramodtoraskar: The following test failed, say
Full PR test history. Your PR dashboard. Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes-sigs/prow repository. I understand the commands that are listed here. |
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Thank you @jiridanek, Truly appreciate moving to next issue and contribution to notebook. |
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Description
This PR fixes Issue #2077 by removing the unused
import tensorboardstatement from the test notebook.Changes Made
import tensorboardfromjupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynbWhy This Change
tensorboardimport was not being used directlytf.keras.callbacks.TensorBoardTesting
Closes #2077
Summary by CodeRabbit