EquationLearner module

class nnodely.layers.equationlearner.EquationLearner(functions: list, *, linear_in: Linear | None = None, linear_out: Linear | None = None)[source]

Represents a nnodely implementation of the Task-Parametrized Equation Learner block.

See also

Task-Parametrized Equation Learner official paper: Equation Learner

Parameters:

functions (list) – A list of callable functions to be used as activation functions.
linear_in (Linear, optional) – A Linear layer to process the input before applying the activation functions. If not provided a random initialized linear layer will be used instead.
linear_out (Linear, optional) – A Linear layer to process the output after applying the activation functions. Can be omitted.

relation_name

The name of the relation.

Type:: str

linear_in

The Linear layer to process the input.

Type:: Linear or None

linear_out

The Linear layer to process the output.

Type:: Linear or None

functions

The list of activation functions.

Type:: list

func_parameters

A dictionary mapping function indices to the number of parameters they require.

Type:: dict

n_activations

The total number of activation functions.

Type:: int

Examples

Basic usage:

x = Input('x')

equation_learner = EquationLearner(functions=[Tan, Sin, Cos])
out = Output('out', equation_learner(x.last()))

Passing a linear layer:

x = Input('x')

linear_layer = Linear(
    output_dimension=3,
    W_init=init_constant,
    W_init_params={'value': 0}
)

equation_learner = EquationLearner(
    functions=[Tan, Sin, Cos],
    linear_in=linear_layer
)

out = Output('out', equation_learner(x.last()))

Passing a custom parametric function and multiple inputs:

x = Input('x')
F = Input('F')

def myFun(K1, p1):
    return K1 * p1

K = Parameter('k', dimensions=1, sw=1, values=[[2.0]])
parfun = ParamFun(myFun, parameters=[K])

equation_learner = EquationLearner([parfun])
out = Output('out', equation_learner((x.last(), F.last())))

For more examples of how to use the equation learner module, please refer to the EquationLearner tutorial.