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f29060491e
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feat(datagen): add dataset generation CLI with sharding and checkpointing
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- Add solver/datagen/dataset.py with DatasetConfig, DatasetGenerator,
ShardSpec/ShardResult dataclasses, parallel shard generation via
ProcessPoolExecutor, checkpoint/resume support, index and stats output
- Add scripts/generate_synthetic.py CLI entry point with Hydra-first
and argparse fallback modes
- Add minimal YAML parser (parse_simple_yaml) for config loading
without PyYAML dependency
- Add progress display with tqdm fallback to print-based ETA
- Update configs/dataset/synthetic.yaml with shard_size, checkpoint_every
- Update solver/datagen/__init__.py with DatasetConfig, DatasetGenerator
exports
- Add tests/datagen/test_dataset.py with 28 tests covering config,
YAML parsing, seed derivation, end-to-end generation, resume,
stats/index structure, determinism, and CLI integration
Closes #10
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2026-02-03 08:44:31 -06:00 |
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363b49281b
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build: phase 0 infrastructure setup
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- Project structure: solver/, freecad/, export/, configs/, scripts/, tests/, docs/
- pyproject.toml with dependency groups: core, train, freecad, dev
- Hydra configs: dataset (synthetic, fusion360), model (baseline, gat), training (pretrain, finetune), export (production)
- Dockerfile with CUDA+PyG GPU and CPU-only targets
- docker-compose.yml for train, test, data-gen services
- Makefile with targets: train, test, lint, format, type-check, data-gen, export, check
- Pre-commit hooks: ruff, mypy, conventional commits
- Gitea Actions CI: lint, type-check, test on push/PR
- README with setup and usage instructions
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2026-02-02 13:26:38 -06:00 |
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