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# to you under the Apache License, Version 2.0 (the
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source("src/test/scripts/functions/federated/paramserv/TwoNNwithNbatches.dml") as TwoNNwithNbatches
source("src/test/scripts/functions/federated/paramserv/CNNwithNbatches.dml") as CNNwithNbatches

# create federated input matrices
features = read($features)
labels = read($labels)

if($network_type == "TwoNN") {
  model = TwoNNwithNbatches::train_paramserv(features, labels, matrix(0, rows=100, cols=784), matrix(0, rows=100, cols=10), 0, $epochs, $utype, $freq, $batch_size, $scheme, $runtime_balancing, $weighting, $eta, $seed, $nbatches)
  print("Test results:")
  [loss_test, accuracy_test] = TwoNNwithNbatches::validate(matrix(0, rows=100, cols=784), matrix(0, rows=100, cols=10), model, list())
  print("[+] test loss: " + loss_test + ", test accuracy: " + accuracy_test + "\n")
}
else {
  model = CNNwithNbatches::train_paramserv(features, labels, matrix(0, rows=100, cols=784), matrix(0, rows=100, cols=10), 0, $epochs, $utype, $freq, $batch_size, $scheme, $runtime_balancing, $weighting, $eta, $channels, $hin, $win, $seed, $nbatches)
  print("Test results:")
  hyperparams = list(learning_rate=$eta, C=$channels, Hin=$hin, Win=$win)
  [loss_test, accuracy_test] = CNNwithNbatches::validate(matrix(0, rows=100, cols=784), matrix(0, rows=100, cols=10), model, hyperparams)
  print("[+] test loss: " + loss_test + ", test accuracy: " + accuracy_test + "\n")
}
