Error using trainNetwork (line 184) Invalid network. Error in one (line 38) trainedNet = trainNetwo​rk(imdsTra​in,layers,​opts)

I am trying to use the predefiend function of googlenet for image classification. But I am getting this error. please can anyone help me out of this.

numClasses = numel(categories(imdsTrain.Labels));

layers = [

layers

fullyConnectedLayer(numClasses,'WeightLearnRateFactor',20,'BiasLearnRateFactor',20)

softmaxLayer

classificationLayer];

%

% Create augmentedImageDatastore from training and test sets to resize

% images in imds to the size required by the network.

imageSize = net.Layers(1).InputSize;

augmentedTrainingSet = augmentedImageDatastore(imageSize, imdsTrain);

augmentedTestSet = augmentedImageDatastore(imageSize, imdsValidation);

%

opts = trainingOptions('sgdm','Plots','training-progress','ValidationData',augmentedTestSet, 'InitialLearnRate', 0.001, 'MaxEpochs', 10, 'MiniBatchSize', 64);

%trainedNet = trainNetwork(imdsTrain,layers,opts);

net = trainNetwork(augmentedTrainingSet, layers, opts);

predictedLabels = classify(net, augmentedTestSet);

testLabels = imdsValidation.Labels;

Error using trainNetwork (line 184)

Invalid network.

Error in one (line 38)

trainedNet = trainNetwork(imdsTrain,layers,opts);

Caused by:

Network: Too many output layers. The network must have one output layer.

Detected output layers:

layer 'output'

layer 147

Layer 'inception_3a-3x3_reduce': Input size mismatch. Size of input to this

layer is different from the expected input size.

Inputs to this layer:

from layer 'inception_3a-relu_1x1' (size 28(S) × 28(S) × 64(C) × 1(B))

Layer 'inception_3a-output': Unconnected input. Each layer input must be

connected to the output of another layer.

Detected unconnected inputs:

Answer 1

[Divya Gaddipati]

You can refer to this example to know more about how to define a network for training:

https://www.mathworks.com/help/deeplearning/ug/train-deep-learning-network-to-classify-new-images.html