Unrecognized function or variable 'invertResidualLayer'

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NoYeah
NoYeah 2023-3-17
评论： NoYeah 2023-3-20
I have installed add-on
'Deep Learning Toolbox' and 'Deep Learning Toolbox model for mobilenetv2'
and used the below code
net = mobilenetv2; % Load pretrained MobileNet model
numClasses = numel(classNames);
layers = [
net.Layers(1:end-3)
fullyConnectedLayer(numClasses,'Name','fc')
softmaxLayer('Name','softmax')
classificationLayer('Name','classoutput')];
options = trainingOptions('adam', ...
'MaxEpochs',10, ...
'MiniBatchSize',32, ...
'ValidationData',imdsValidation, ...
'ValidationFrequency',5, ...
'InitialLearnRate',1e-4, ...
'LearnRateSchedule','piecewise', ...
'LearnRateDropFactor',0.1, ...
'LearnRateDropPeriod',5, ...
'L2Regularization',0.01, ...
'Plots','training-progress');
% Train the network
net = trainNetwork(imdsTrain,layers,options);
and I got the error message below
Error using trainNetwork
invalid network.
caused by:
Layer 'block_11_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_12_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_14_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_15_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_2_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_4_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_5_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_7_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_8_add' Unconnected input. Each layer input must be connected to the output of
another layer.
Layer 'block_9_add' Unconnected input. Each layer input must be connected to the output of
another layer.
I don`t know why this error happens...
maybe using pretrained model intrigue error depends on the data?
How to solve this error?

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采纳的回答

Pratham Shah
Pratham Shah 2023-3-17
Hi,
I have struggled with this issue a lot and I know the reason behind it.
The problem is while you are calling 'net.Layers(1:end-3)' it will only have information of layers, not the connections and the problem is occuring in addition layer as it requires 2 inputs but the layer graph is skipping one connection in net.Layer.
I don't have any permenent solution to that but you can try 2 things:
  1. Import the 'net' in the Network Designer Application and export the 'lgraph' after replacing last 3 layers with your desired layer.
  2. You can use 'connectLayer' manually for all the unconnected layers like this,
lgraph = layerGraph(layers);
lgraph = connectLayers(lgraph,'input','add/in2');
but this process will take lot of time.
But by looking at you code I think you can just use the 'replaceLayer' in last layer(to match the number of classes) because mobilenetv2 already have fc and softmax function.
P.S. : Hope this helps :)

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