def MLP(ls, cost) :
	
	i = ML.Input(28*28, name = 'inp')
	h = ML.Hidden(500, activation = MA.Tanh(), decorators = [MD.BinomialDropout(0.2)], initializations = [MI.GlorotTanhInit()], regularizations = [ MR.L1(0), MR.L2(0.0001) ], name = "hid" )
	o = ML.SoftmaxClassifier(10, initializations = [MI.ZerosWeights()], learningScenario = ls, costObject = cost, name = "out", regularizations = [ MR.L1(0), MR.L2(0.0001) ] )

	mlp = h > o > i
	
	return mlp
dataset/ETHPy150Open tariqdaouda/Mariana/Mariana/examples/vanilla_mnist_perceptron_mlp.py/MLP/swapped operands of `>`