pymoto.Module

class pymoto.Module

Main class: Module Transforms input signal to output signal and output signal sensitivity to input signal sensitivity

Initialize using Module() >> Module(input, output)

Multiple inputs and outputs: >> Module([input1, input2], [output1, output2])

No tag: >> Module([input1, input2], [output1, output2])

No outputs: >> Module([inputs])

Using keywords: >> Module(sig_in=[inputs], sig_out=[outputs])

Methods

`__init__`()
`connect`(sig_in[, sig_out])	Connect without automatic adding to a function network
`get_input_sensitivities`([as_list])
`get_input_states`([as_list])
`get_output_sensitivities`([as_list])
`get_output_states`([as_list])
`reset`()	Reset the state of the sensitivities (they are set to zero or to None)
`response`()	Calculate the response from sig_in and output this to sig_out
`sensitivity`()	Calculate sensitivities using backpropagation

Attributes

`n_in`	Get the number of input signals
`n_out`	Get the number of output signals
`sig_in`
`sig_out`

connect(sig_in: Signal | Iterable[Signal], sig_out: Signal | Iterable[Signal] = None): Connect without automatic adding to a function network

property n_out: int

Get the number of output signals

Note: Cannot be used in the initial __call__()

sensitivity()

Calculate sensitivities using backpropagation

Based on the sensitivity we get from sig_out, reverse the process and output the new sensitivities to sig_in

reset(): Reset the state of the sensitivities (they are set to zero or to None)