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How can i fix the error mismatch format when convert multiplication layer from LayerGraph to dlnetwork in prune and quantize network example

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I have some problems when getting used to MATLAB's Prune and Quantize Semantic Segmentation Network example at
My custom LayerGraph network has a multiplication layer whose 2 input are 64(S) x 64(S) x 64( C) x 1(B) and 64(S) x 1(B), when accessing the dlnetwork function in the Prune section, I received an error message saying input format mismatch for this layer:
"Layer 'layer': For function layers with Formattable set to false, all inputs must have the same format. To enable support for multiple inputs with different formats, use a function layer with Formattable set to true."
I tried changing the Formattable property for this class to true and it worked, here is my custom multiplication layer to change the Formattable property.
function output = myPredictionFunction(input1, input2)
output = input1 .* input2;
here is my code for use it:
multiplication = functionLayer(@myPredictionFunction ,'Formattable', true);
lgraph = replaceLayer(lgraph,'layer',multiplication,'ReconnectBy','name');
trainedNet = dlnetwork(lgraph);
but, when using the calibrate() function in the Quantize section,
eqNet = equalizeLayers(prunedNet);
quantizableNet = dlquantizer(prunedNet,ExecutionEnvironment="GPU");
I got the error:
"Error using dlquantizer/calibrate. For code generation of layer 'layer', 'Formattable' must be false."
I tried setting the Formattable to False and adjusting both inputs of the multiplication layer to 64(S) x 64(S) X 64(C) X 1(B) but the format mismatch error still persists when using dlnetwork() function.
Here is my layer to adjusting format of multiplication layer's input:
classdef RepeatValuesLayer < nnet.layer.Layer
% Custom layer to repeat values along spatial dimensions
function layer = RepeatValuesLayer(name)
% Construct a RepeatValuesLayer
% Set name
layer.Name = name;
% Set description
layer.Description = "Repeat values along spatial dimensions";
function Z = predict(~, X)
% Predict method
Z = repmat(X, [64, 64, 1]);
and the result in LayerGraph:
i dont know what to do to fix this issues

Answers (2)

Joss Knight
Joss Knight on 29 Mar 2024
That's an annoying limitation which is hopefully fixed in current releases. Is there any particular reason why you can't use multiplicationLayer? I presume it's the dimension expansion.

Joss Knight
Joss Knight on 29 Mar 2024
For one solution, replace the fully connected layers with convolution layers with filters the size of the input and num filters equal to the number of fully connected outputs. So I think 1x1x64x4 and 1x1x4x64 in your case. So basically one 2-d conv size 1 with 4 filters and one with 64 filters. That should ensure everything has the same dimension at the multiplication and you can use multiplicationLayer too.

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