Custom Layer- Incorrent number of outputs

2 visualizaciones (últimos 30 días)
Valentin Steininger
Valentin Steininger el 9 de Ag. de 2019
Comentada: Valentin Steininger el 9 de Ag. de 2019
Hi,
I'm trying to create a custom intermediate layer that can split up data. When I use checkLayer to validate the functionality it throws the error: "Incorrect number of output arguments for 'predict' in Layer splitDataLayer. Expected to have 1, but instead it has 4." although I've set the number of Outputs to 4 in the constructor.
classdef splitDataLayer < nnet.layer.Layer
methods
function obj = splitDataLayer(name)
obj.Name = name;
obj.numOutputs = 4;
obj.OutputNames = {'out1','out2','out3','out4'};
end
function [Z1, Z2, Z3, Z4] = predict(~, X)
Z1 = X(1, :, :, :);
Z2 = X(2, :, :, :);
Z3 = X(3, :, :, :);
Z4 = X(4, :, :, :);
end
function [dLdX] = backward(~,~,~,~,~,~,dLdZ1,dLdZ2,dLdZ3,dLdZ4,~)
dLdX = cat(1, dLdZ1,...
dLdZ2,...
dLdZ3,...
dLdZ4);
end
end
end
As can be seen above, both the number of outputs as well as the output matrix in the predict function have been set correctly. So I don't know what could be wrong about the code and cause that error.
I would be happy for any help!

Respuesta aceptada

Maria Duarte Rosa
Maria Duarte Rosa el 9 de Ag. de 2019
Hi Valentin,
Thank you for your question.
Multi-input/Multi-output custom layers are supported from R2019a. From your error message I suspect you are on a older release.
Your layer looks good though, apart from obj.numOutputs = 4; which should be obj.NumOutputs = 4;
When I correct for that all the checkLayer tests pass in R2019a:
layer = splitDataLayer('test');
validInputSize = [4 5 20 4]; % Some arbitrary dimensions
checkLayer(layer,validInputSize,'ObservationDimension',4)
Running nnet.checklayer.TestCase
.......... .......... ....
Done nnet.checklayer.TestCase
__________
Test Summary:
24 Passed, 0 Failed, 0 Incomplete, 0 Skipped.
Time elapsed: 1.3818 seconds.
I hope this helps.
  1 comentario
Valentin Steininger
Valentin Steininger el 9 de Ag. de 2019
Hi Maria,
I also just realized that it's not available on 2018b as I tried the "custom weighted addition layer" example from the documenation and it threw the same error.
I'm just about to upgrade to 2019a.
Thanks for the answer!

Iniciar sesión para comentar.

Más respuestas (0)

Categorías

Más información sobre Sequence and Numeric Feature Data Workflows en Help Center y File Exchange.

Productos


Versión

R2018b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by