Deep Learning Train Bayesian Neural Network

when I use the MATLAB TrainBayesianNeuralNetworkUsingBayesByBackpropExample

I can work with good results as it was offered

However, when I copied this code to m.file , named demo_BNN

I have found lots of problems

in Train model section

mbq = minibatchqueue(dsTrain, ...

MiniBatchSize= miniBatchSize, ...

MiniBatchFcn= @preprocessMiniBatch, ...

MiniBatchFormat=["SSCB" "CB"]);

Error using minibatchqueue>iValidateMiniBatchFcn

Invalid value for 'MiniBatchFcn'. Unable to find function 'preprocessMiniBatch'.

Error in minibatchqueue>iParseInputs (line 786)

iValidateMiniBatchFcn(options.MiniBatchFcn, numVariables, options.NumOutputs);

Error in minibatchqueue (line 288)

options = iParseInputs(numVariables, varargin{:});

Error in demo_BNN (line 82)

mbq = minibatchqueue(dsTrain, ...

However, there are similar operations from document of minibatchqueue

SImilaraly, In monitor section

[elboLoss,rmsError,gradientsNet,gradientsNoise] = dlfeval(@modelLoss, ...

net,X,T,samplingNoise,miniBatchIdx,numIterationsPerEpoch);

Undefined function 'modelLoss' for input arguments of type 'dlnetwork'.

Error in deep.internal.dlfeval (line 17)

[varargout{1:nargout}] = fun(x{:});

Error in deep.internal.dlfevalWithNestingCheck (line 19)

[varargout{1:nargout}] = deep.internal.dlfeval(fun,varargin{:});

Error in dlfeval (line 31)

[varargout{1:nargout}] = deep.internal.dlfevalWithNestingCheck(fun,varargin{:});

Error in demo_BNN (line 123)

[elboLoss,rmsError,gradientsNet,gradientsNoise] = dlfeval(@modelLoss, ...

Answer 1

[Yash]

Hi Joy,

I tried reproducing the errors on my end. However, "demo_BNN.mlx" is working fine for me. I created a copy of "TrainBayesianNeuralNetworkUsingBayesByBackpropExample.mlx" and renamed it to "demo_BNN.mlx".

Ensure the following to try to resolve the errors:

• Check that all the supporting functions ("preprocessMiniBatch", "modelPosteriorSample", "logLikelihood", "modelLoss", "negativeELBO", "averageNegativeELBO" and "KLWeight") are defined at the end of "demo_BNN.mlx". These functions are defined in "TrainBayesianNeuralNetworkUsingBayesByBackpropExample.mlx".
• Check that all the helper .M files are present in the same directory as "demo_BNN.mlx". These files are "bayesFullyConnectedLayer.m", "initializeGlorot.m" and "logProbabilityNormal.m". These files are present in the same directory as "TrainBayesianNeuralNetworkUsingBayesByBackpropExample.mlx".

Attaching "demo_BNN.mlx" and other helper functions for your reference.