---

name: helpers description: "Routes LabML helper training loops, metrics, device/optimizer configs, datasets, and remote dataset workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

Helpers

Use this subskill for labml_helpers: configurable training loops, datasets, metrics, device selection, optimizer selection, model wrappers, and the remote dataset client/server pair.

Use this when

• The task mentions labml_helpers, DeviceConfigs, OptimizerConfigs, TrainingLoopConfigs, TrainValidConfigs, SimpleTrainValidConfigs, MNISTConfigs, CIFAR10Configs, Accuracy, Collector, RecallPrecision, SeedConfigs, or Module.
• The user wants a reusable supervised-training skeleton, a metric module, or a device/optimizer config wrapper.
• The user wants to serve a dataset over HTTP with DatasetServer or consume it with RemoteDataset.

Boundaries

Include:

• Training-loop abstractions and config classes.
• Metric modules and stateful helper patterns.
• Device and optimizer configs.
• Dataset helpers, including the remote dataset server/client pair.
• Small supervised-learning recipes that stay within the helper package.

Exclude or route elsewhere:

• Client-side logging and monitoring helpers → tracking.
• SSH, rsync, or remote job orchestration → remote.
• FastAPI app backend and monitoring UI routes → server.

Read next

• references/api-reference.md for the verified helper classes and signatures.
• references/workflows.md for small training-loop recipes and the remote dataset pattern.
• references/troubleshooting.md for torch, dataset, device, and remote-dataset failures.
• scripts/helpers_smoke.py for a safe synthetic training check.
• scripts/remote_dataset_smoke.py for a local loopback check of the dataset server/client pair.

Typical routes

Build a reusable supervised trainer

Choose this route for SimpleTrainValidConfigs, BatchIndex, Trainer, or metric state modules.

Choose a device or optimizer

Choose this route for DeviceConfigs, DeviceInfo, OptimizerConfigs, or NoamOpt.

Use packaged datasets

Choose this route for MNISTConfigs, CIFAR10Configs, or helpers that build PyTorch DataLoader objects.

Share a dataset remotely

Choose this route for DatasetServer, RemoteDataset, and the FastAPI/uvicorn loopback pattern.