Training Loop

braintools.trainer is a lightweight, PyTorch-Lightning-style training loop for brainstate models: a LightningModule defines the training, validation and test steps, and a Trainer runs them with batching, a jit-compiled gradient step, callbacks, checkpoints and logging. The module is in maintenance mode: bugs are fixed, but no new features are planned.

What you’ll find here

• A training loop tutorial: a small classifier written as a LightningModule, DataLoader batching of plain arrays, validation metrics, EarlyStopping, ModelCheckpoint with save_top_k, a CSVLogger whose metrics.csv is read back with pandas and plotted, inspecting a checkpoint with load_checkpoint, and evaluating a fresh model from the best checkpoint with Trainer.test(..., ckpt_path=...) and Trainer.predict.

For the full list of classes and parameters, see the API reference.

• A training loop with braintools.trainer