- class sinabs.layers.ExpLeakSqueeze(batch_size=None, num_timesteps=None, **kwargs)#
ExpLeak layer with 4-dimensional input (Batch*Time, Channel, Height, Width).
Same as parent ExpLeak class, only takes in squeezed 4D input (Batch*Time, Channel, Height, Width) instead of 5D input (Batch, Time, Channel, Height, Width) in order to be compatible with layers that can only take a 4D input, such as convolutional and pooling layers.
Input: \((Batch \times Time, Channel, Height, Width)\) or \((Batch \times Time, Channel)\)
Output: Same as input.
The membrane potential resets according to reset_fn for every spike.
This attribute is only available if tau_syn is not None.
- forward(input_data: torch.Tensor) torch.Tensor #
Forward call wrapper that will flatten the input to and unflatten the output from the super class forward call.
input_data (torch.Tensor) –
- Return type