Trainer

encoding.trainer.AbstractTrainer orchestrates the full pipeline:

• Extract and downsample features per story

• Apply FIR delays

• Structure data (concat or train/test split)

• Fit a model and log/save results

Configuration

Key constructor arguments:

• assembly: provides stories, brain/ timing arrays

• feature_extractors: list of extractors from the factory

• downsampler: aligns to TRs

• model: must implement fit_predict

• fir_delays: list of sample delays

• trimming_config: indices for trimming

• use_train_test_split: bool, Lebel vs concatenated

• dataset_type: e.g., narratives, used for caching keys

• logger_backend: wandb or tensorboard

Outputs

Returns a metrics dict with common fields: median_score, mean_score, std_score and optionally correlations, significant_mask.