AutoKeras repo skill
SkillProductivity"Use AutoKeras for Keras-based AutoML task APIs, custom AutoModel
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Then ask your AI: use the AutoKeras repo skill skill
What this skill tells your AI
The instructions your AI receives, as published by vectorspacelab/arex-skill in skills/repositories/repo-skills/autokeras/SKILL.md and read by ahel’s review.
Use this skill when a user asks how to operate AutoKeras: Keras-based AutoML for image, text, structured-data, custom search-space, tuner, and export workflows. This skill is self-contained; do not rely on the original repository checkout at runtime.
Setup first
AutoKeras 3.0.0 uses Keras 3. Choose and install a Keras backend before importing Keras or AutoKeras. The repository's public install guidance and CI support a PyTorch backend path for ordinary CPU checks.
python -m pip install autokeras
python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
KERAS_BACKEND=torch python -c "import keras, autokeras as ak; print(ak.__version__, keras.backend.backend())"
Run scripts/check_autokeras_env.py when setup, backend, import, or public API visibility is uncertain.
Route by task
- sub-skills/task-apis/SKILL.md: high-level
ImageClassifier,ImageRegressor,TextClassifier,TextRegressor,StructuredDataClassifier, andStructuredDataRegressorworkflows, including data shapes and task-specific troubleshooting. - sub-skills/automodel-customization/SKILL.md: custom
AutoModelgraphs, nodes, blocks, heads, multimodal inputs, multitask outputs, and graph/data ordering failures. - sub-skills/search-and-export/SKILL.md: tuner names/classes,
max_trials, objectives, callbacks, search directories,overwrite,export_model(), and reloading saved.kerasmodels.
Shared references
- references/setup-and-troubleshooting.md: installation/backend checks, common import failures, optional GPU notes, and cross-cutting recovery.
- references/source-script-inventory.md: how repository examples/scripts were distilled into bundled helpers or excluded.
- references/repo-provenance.md: source snapshot used to build this skill; read it before deciding whether a checkout needs
refresh-repo-skill. - references/repo-routing-metadata.json: structured metadata consumed by the repo-skills router importer.
Operating constraints
- Keep first runs bounded:
max_trials=1,epochs=1, small synthetic/local data, and an explicit scratchdirectory. - Set
KERAS_BACKENDbefore importing Keras or AutoKeras. - Do not run original examples, notebooks, benchmark scripts, Docker scripts, or release tooling as runtime dependencies. Use bundled scripts and references instead.
- CUDA/GPU execution is optional for this skill. Do not claim GPU verification unless the user's own environment and backend framework have been checked.
Signals
- GitHub stars
- 266
- Forks
- 21
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packagesK6low
bundled executables the agent is told to runK1binfo
installs-packages (in references/setup-and-troubleshooting.md)
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Catalog kind
- skill
- Gateway key
autokeras- Source
- github.com/vectorspacelab/arex-skill