neuraltrain.models.reve.NtReve

class neuraltrain.models.reve.NtReve(*, kwargs: dict[str, Any] = {}, from_pretrained_name: str | None = None, channel_mapping: dict[str, str] | None = None)[source][source]

Config for the braindecode REVE model with channel-mapping support.

Extends BaseBrainDecodeModel with REVE-specific logic:

  1. Channel remapping – an explicit channel_mapping dict maps dataset channel names to REVE position-bank names. Channels whose names already appear in the bank (exact match) need no entry.

  2. Pretrained loading – bypasses the base-class restriction on n_times for pretrained models, since REVE needs it to size its final_layer.

  3. Encoder-only output – when n_outputs is None (downstream wrapper handles the head), the model is wrapped to call forward(return_output=True) and return the final transformer layer output, bypassing REVE’s final_layer.

Parameters:

channel_mapping (dict or None) – Explicit mapping from dataset channel names to REVE position-bank names. Useful for EEG systems whose naming convention is absent from the bank (e.g. Neuromag "EEG 005" or easycap-M10 numeric "2").