Unable to read file on AWS S3

I am getting an error when trying to access files in our S3 bucket for training a neural network for image classification. I have set the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY properly, and can retrieve an image and view it in MATLAB with imshow. However, when trying to execute the trainNetwork function it crashes with an "unable to read file..." message. Here is the relevant code up until the line in which it crashes:

%% set up net

setenv('AWS_ACCESS_KEY_ID','XXXXXXXXXXXXXXXX');
setenv('AWS_SECRET_ACCESS_KEY','XXXXXXXXXXXXXXXXXXX')

% start cluster
c=parcluster
start(c)

numberOfWorkers = 1;

% set network architecture
 net=resnet50;
 lgraph = layerGraph(net);
 
[learnableLayer,classLayer] = findLayersToReplace(lgraph);
[learnableLayer,classLayer] 

newLearnableLayer = fullyConnectedLayer(2, ...
        'Name','new_fc', ...
        'WeightLearnRateFactor',10, ...
        'BiasLearnRateFactor',10);
    
lgraph = replaceLayer(lgraph,learnableLayer.Name,newLearnableLayer); 

newClassLayer = classificationLayer('Name','new_classoutput');
lgraph = replaceLayer(lgraph,classLayer.Name,newClassLayer);

figure('Units','normalized','Position',[0.3 0.3 0.4 0.4]);
plot(lgraph)
ylim([0,20])

layers = lgraph.Layers;
connections = lgraph.Connections;

layers(1:10) = freezeWeights(layers(1:10));
lgraph = createLgraphUsingConnections(layers,connections);

pixelRange = [-30 30];
scaleRange = [0.9 1.1];
imageAugmenter = imageDataAugmenter( ...
    'RandXReflection',true, ...
    'RandYReflection',true, ...
    'RandRotation',[-180 180], ...
    'RandXTranslation',pixelRange, ...
    'RandYTranslation',pixelRange, ...
    'RandXShear',[0 20], ...
    'RandYShear',[0 20],...
    'RandScale',scaleRange ...
    );

%%
pool = parpool('EnvironmentVariables',["AWS_ACCESS_KEY_ID","AWS_SECRET_ACCESS_KEY"]);
%%
baseFd='E:\AI Training images\Results\';

baseFds3='s3://rumitestbucket/';
    
cd([baseFd])

TrainFd=[baseFds3,'train/']    
    
imds = imageDatastore(TrainFd, ...
 'IncludeSubfolders',true, ...
 'FileExtensions','.tif', ...
 'LabelSource','foldernames');

[imdsTrain,imdsValidation] = splitEachLabel(imds,0.8,0.2);

augimdsTrain = augmentedImageDatastore(net.Layers(1).InputSize(1:2),imdsTrain, ...
    'DataAugmentation',imageAugmenter);

augimdsValidation = augmentedImageDatastore(net.Layers(1).InputSize(1:2),imdsValidation);

miniBatchSize = 12;
valFrequency = floor(numel(augimdsTrain.Files)/miniBatchSize);

options = trainingOptions('sgdm', ...
    'ExecutionEnvironment','parallel', ...
    'MiniBatchSize',miniBatchSize, ...
    'MaxEpochs',40, ...
    'InitialLearnRate',3e-4, ...
    'Shuffle','every-epoch', ...
    'ValidationData',augimdsValidation, ...
    'ValidationFrequency',valFrequency, ...
    'Verbose',false, ...
    'Plots','training-progress');

[TrainedNet,info] = trainNetwork(augimdsTrain,lgraph,options);

And this is the error message:

Error using trainNetwork (line 184)

Unable to read file: 's3://rumitestbucket/train/RUES2_training/E03_col19.tif'.

Caused by:

Error using nnet.internal.cnn.DistributedDispatcher/computeInParallel (line 193)

Error detected on worker 1.

Error using matlab.io.datastore.ImageDatastore/read (line 77)

Unable to read file: 's3://rumitestbucket/train/RUES2_training/E03_col19.tif'.

Unable to use a value of type string as an index.

-------------------------------

Any help would be very appreciated!

[Joss Knight]

So you can read your dataset on your client MATLAB? e.g.

reset(augimdsTrain);
while hasdata(augimdsTrain)
    read(augimdsTrain);
end

[Rumi Scientific]

Yes, access to the dataset is fine. I have the same issue when I run the MATLAB example https://www.mathworks.com/help/deeplearning/ug/train-a-network-in-the-cloud-using-built-in-parallel-support.html

It crashes at the same point, with the same error message (with the test images loaded in our s3 bucket as described here: https://www.mathworks.com/help/deeplearning/ug/upload-deep-learning-data-to-the-cloud.html).

I tried the commands you suggested above:

reset(augmentedImdsTrain)
while hasdata(augmentedImdsTrain)
    read(augmentedImdsTrain)
end

And it has been 'busy' for several minutes while it accesses the thousands of images (I left off the last semi-colon to ensure it was reading them).