norse.torch.functional.lif_correlation module

class norse.torch.functional.lif_correlation.LIFCorrelationParameters(lif_parameters, input_correlation_parameters, recurrent_correlation_parameters)

Bases: tuple

Create new instance of LIFCorrelationParameters(lif_parameters, input_correlation_parameters, recurrent_correlation_parameters)

input_correlation_parameters: norse.torch.functional.correlation_sensor.CorrelationSensorParameters

Alias for field number 1

lif_parameters: norse.torch.functional.lif.LIFParameters

Alias for field number 0

recurrent_correlation_parameters: norse.torch.functional.correlation_sensor.CorrelationSensorParameters

Alias for field number 2

class norse.torch.functional.lif_correlation.LIFCorrelationState(lif_state, input_correlation_state, recurrent_correlation_state)

Bases: tuple

Create new instance of LIFCorrelationState(lif_state, input_correlation_state, recurrent_correlation_state)

input_correlation_state: norse.torch.functional.correlation_sensor.CorrelationSensorState

Alias for field number 1

lif_state: norse.torch.functional.lif.LIFState

Alias for field number 0

recurrent_correlation_state: norse.torch.functional.correlation_sensor.CorrelationSensorState

Alias for field number 2

norse.torch.functional.lif_correlation.lif_correlation_step(input_tensor, state, input_weights, recurrent_weights, p=LIFCorrelationParameters(lif_parameters=LIFParameters(tau_syn_inv=tensor(200.), tau_mem_inv=tensor(100.), v_leak=tensor(0.), v_th=tensor(1.), v_reset=tensor(0.), method='super', alpha=tensor(100.)), input_correlation_parameters=CorrelationSensorParameters(eta_p=tensor(1.), eta_m=tensor(1.), tau_ac_inv=tensor(10.), tau_c_inv=tensor(10.)), recurrent_correlation_parameters=CorrelationSensorParameters(eta_p=tensor(1.), eta_m=tensor(1.), tau_ac_inv=tensor(10.), tau_c_inv=tensor(10.))), dt=0.001)

Return type

Tuple[Tensor, LIFCorrelationState]