Intermediate Examples

These examples assume familiarity with the basic tier and introduce the storage layer, performance monitoring, and more complex pipeline patterns. Training examples are labeled explicitly in this list; if the collection grows further, split training workflows into a dedicated examples section so inference, dynamics, and training entry points remain easy to scan.

01 — Multi-Stage Pipeline: FusedStage composition, LoggingHook CSV output, step-budget migration, fused hooks for global status monitoring.

02 — Trajectory I/O: Writing trajectories to Zarr, reading back with DataLoader, round-trip validation.

03 — NPT MD: Pressure-controlled dynamics with the MTK barostat, LJ stress computation, cell fluctuation monitoring.

04 — Inflight Batching: SizeAwareSampler, Mode 2 FusedStage run (batch=None), system_id tracking, ConvergedSnapshotHook collecting results.

05 — Safety and Monitoring: NaNDetectorHook, MaxForceClampHook, EnergyDriftMonitorHook, StageTimingHook — defensive MD patterns.

06 — DDP MLP Training: DDPHook with a simple MLP, dummy AtomicData, single-node torchrun launch, and auto/gloo/nccl backend selection.

07 — Rich Training Reporting: Live Rich dashboard driven by synthetic training losses, validation metrics, progress counters, and learning-rate scheduler values.

Multi-Stage Dynamics Pipelines with FusedStage

Multi-Stage Dynamics Pipelines with FusedStage

Writing and Replaying Trajectories with Zarr

Writing and Replaying Trajectories with Zarr

NPT Barostat Validation: Expansion and Contraction

NPT Barostat Validation: Expansion and Contraction

Processing Large Datasets with Inflight Batching

Processing Large Datasets with Inflight Batching

Defensive MD: Safety Hooks and Performance Monitoring

Defensive MD: Safety Hooks and Performance Monitoring

Distributed Training: DDPHook with a Dummy MLP

Distributed Training: DDPHook with a Dummy MLP

Rich Training Reporting

Rich Training Reporting