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gradients = function (matrix[double] input) return (matrix[double] output) {
	output = input + 1;
}

aggregation = function (matrix[double] input) return (matrix[double] output) {
  output = input + 1;
}

model = list(e1="element1")
X = matrix(1, 2, 3)
Y = matrix(2, 2, 3)
X_val = matrix(3, 2, 3)
Y_val = matrix(4, 2, 3)
hps = list(e2="element2")

# Use paramserv function
supd = ".defaultNS::gradients";
sagg = "XXX::aggregation";
model = paramserv(model=model, features=X, labels=Y, val_features=X_val, val_labels=Y_val,
  upd=supd, agg=sagg, mode="LOCAL", utype="BSP", freq="EPOCH", epochs=10, hyperparams=hps)

print(toString(model))