braindecode.models.InterpolatedModel#

braindecode.models.InterpolatedModel(model_cls, target_chs_info, name=None)[source]#

Return a subclass of model_cls that interpolates channels to target_chs_info.

Warning

Experimental. Public API may change without a deprecation cycle.

Parameters:

  • model_cls (Type) – A braindecode model class (subclass of EEGModuleMixin).

  • target_chs_info (list[dict]) – The canonical channel set the backbone expects internally. Every instance of the returned class projects its input channels to this set via ChannelInterpolationLayer.

  • name (Optional[str]) – __name__ to assign to the returned class. Defaults to f"Interpolated{model_cls.__name__}".

Returns:

A new subclass of model_cls whose __init__ accepts arbitrary user chs_info and automatically inserts a frozen (by default) channel-interpolation layer before the backbone.

Return type:

Type

Examples using braindecode.models.InterpolatedModel#

Loading Pretrained Foundation Models on Arbitrary Channel Sets

Loading Pretrained Foundation Models on Arbitrary Channel Sets