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Error using activations functions in matlab

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I trying to replace the pre-trained CNN fully connected layer with mine 'new_fc'.
imds = imageDatastore('MerchData', 'IncludeSubfolders',true, 'LabelSource','foldernames');
[imdsTrain,imdsValidation] = splitEachLabel(imds,0.7);
testnet = resnet18
inputSize = testnet.Layers(1).InputSize
augimdsTrain = augmentedImageDatastore(inputSize(1:2),imdsTrain)
augimdsValidation = augmentedImageDatastore(inputSize(1:2),imdsValidation)
if isa(learnableLayer,'nnet.cnn.layer.FullyConnectedLayer')
newLearnableLayer = fullyConnectedLayer(7, ...
'Name','new_fc', ...
'WeightLearnRateFactor',10, ...
elseif isa(learnableLayer,'nnet.cnn.layer.Convolution2DLayer')
newLearnableLayer = convolution2dLayer(1,7, ...
'Name','new_conv', ...
'WeightLearnRateFactor',10, ...
lgraph = replaceLayer(lgraph,learnableLayer.Name,newLearnableLayer)
newClassLayer = classificationLayer('Name','new_classoutput')
lgraph = replaceLayer(lgraph,classLayer.Name,newClassLayer)
layer = 'new_fc';
The error message that i got is as below.
"check for incorrect argument data type or missing argument in call to function 'activations'.
Hope someone could help on this. Thank you in advance.

Accepted Answer

yanqi liu
yanqi liu on 23 Mar 2022
yes,sir,if modify net structure,may be need retrain it,then use activations to get feature
so,may be use
featuresTrain = activations(testnet,augimdsTrain,'fc1000','OutputAs','rows')
Teo on 23 Mar 2022
Thanks for the reply. May i comfirm with you again that i need to retrain it first using "trainNetwork" function then only use the following code?
featuresTrain = activations(lgraph,augimdsTrain,layer,'OutputAs','rows')
or i can directly use the followig code without retrain it as you already provide the solution as followed?
featuresTrain = activations(lgraph,augimdsTrain,'new_fc','OutputAs','rows')
Hope you are able to help on this?
Thank you
Teo on 23 Mar 2022
i managed to solve the problem. Thank you for your help.

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