NBeatsGenericNet

class NBeatsGenericNet(input_size: int, output_size: int, loss: torch.nn.modules.module.Module, stacks: int, layers: int, layer_size: int, lr: float, optimizer_params: Optional[Dict[str, Any]] = None)

Bases: etna.models.nn.nbeats.nets.NBeatsBaseNet

N-BEATS generic model.

Initialize N-BEATS model.

Parameters

• input_size (int) – Input data size.

• output_size (int) – Forecast size.

• loss (nn.Module) – Optimisation objective. The loss function should accept three arguments: y_true, y_pred and mask. The last parameter is a binary mask that denotes which points are valid forecasts.

• stacks (int) – Number of block stacks in model.

• layers (int) – Number of inner layers in each block.

• layer_size (int) – Inner layers size in blocks.

• lr (float) – Optimizer learning rate.

• optimizer_params (Optional[Dict[str, Any]]) – Additional parameters for the optimizer.

Attributes