braindecode.modules.CombinedConv#

class braindecode.modules.CombinedConv(in_chans, n_filters_time=40, n_filters_spat=40, filter_time_length=25, bias_time=True, bias_spat=True)[source]#

Merged convolutional layer for temporal and spatial convs in Deep4/ShallowFBCSP

Numerically equivalent to the separate sequential approach, but this should be faster.

Parameters:

  • in_chans (int) – Number of EEG input channels.

  • n_filters_time (int) – Number of temporal filters.

  • filter_time_length (int) – Length of the temporal filter.

  • n_filters_spat (int) – Number of spatial filters.

  • bias_time (bool) – Whether to use bias in the temporal conv

  • bias_spat (bool) – Whether to use bias in the spatial conv

Methods

forward(x: Tensor) → Tensor[source]#

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.