Examples

Each subdirectory of examples/ is a self-contained training recipe. Recipes are nvsubquadratic.lazy_config.LazyConfig trees describing the network, datamodule, Lightning wrapper, and trainer; running them is python -m experiments.run --config <path>.

The active experimental roadmap (priorities, owners, status) lives at examples/overview_tracker.md.

Classification

ImageNet

examples/imagenet_classification/ ships seven CCNN configs (Hyena / Hyena-circular / attention, with and without augmentation, plus tiny variants for laptop sanity checks). Representative entry points: ccnn_7_512_hyena.py, ccnn_7_512_attention.py.

TinyImageNet — ViT-5

examples/vit5_imagenet/ is the ViT-5 baseline suite (v1–v5) with its own TRACKER.md.

Spatial recall

examples/spatial_recall_1d/, spatial_recall_2d/, spatial_recall_3d/, and the newer spatial_recall_v2/ are synthetic recall benchmarks measuring how well each mixer (Hyena, attention, Mamba, CKConv) routes information across long-range spatial/sequence positions. See spatial_recall_v2/TRACKER.md for the v2 task suite.

Benchmarks

examples/vit_b_benchmark/ holds the throughput-comparison configs used to produce the numbers in Benchmarks.

Scientific

The Well

examples/well/ covers The Well PDE benchmark — see its README for sub-datasets and baselines.