def perceptron(size, weights):
"""Creates a perceptron network
"""
inputLayer = Layer(LayerType.INPUT, size[0], activation=None)
outputLayer = Layer(LayerType.OUTPUT, size[1], activation=Neuron.HEAVISIDE)
pp.pprint(weights)
inputLayer.connect(outputLayer, weights)
return Ann({'input': inputLayer, 'hidden': [], 'output': outputLayer})
def connect(layer: Layer, instruction: Instruction):
if len(instruction.details) > 2:
print("\nWRONG CONNECT INSTRUCTION FORMAT.")
raise Exception
port1 = str.split(instruction.details[0], '_')
port2 = str.split(instruction.details[1], '_')
layer.connect(instruction.time, port1[0],
int(port1[1]) - 1, port2[0],
int(port2[1]) - 1)
write(
instruction.time,
"connect, device_x={}, port_x={}, device_y={}, port_y={}\n".format(
port1[0], port1[1], port2[0], port2[1]))
def multi_layer_network(size, weights):
"""Creates a 3 layer network (1 hidden)
"""
inputLayer = Layer(LayerType.INPUT, size[0], activation=None)
hiddenLayer = Layer(LayerType.HIDDEN, size[1], activation=Neuron.LOGISTIC)
outputLayer = Layer(LayerType.OUTPUT, size[2], activation=Neuron.LOGISTIC)
inputLayer.connect(hiddenLayer, weights[1])
hiddenLayer.connect(outputLayer, weights[0])
return Ann({
'input': inputLayer,
'hidden': [hiddenLayer],
'output': outputLayer
})
def deep_network(size, weights):
"""Creates a 5 layer network (3 hidden)
"""
inputLayer = Layer(LayerType.INPUT, size[0], activation=None)
hiddenLayer1 = Layer(LayerType.HIDDEN, size[1], activation=Neuron.LOGISTIC)
hiddenLayer2 = Layer(LayerType.HIDDEN, size[2], activation=Neuron.LOGISTIC)
hiddenLayer3 = Layer(LayerType.HIDDEN, size[3], activation=Neuron.LOGISTIC)
outputLayer = Layer(LayerType.OUTPUT, size[4], activation=Neuron.LOGISTIC)
inputLayer.connect(hiddenLayer1, weights[3])
hiddenLayer1.connect(hiddenLayer2, weights[2])
hiddenLayer2.connect(hiddenLayer3, weights[1])
hiddenLayer3.connect(outputLayer, weights[0])
return Ann({
'input': inputLayer,
'hidden': [hiddenLayer1, hiddenLayer2, hiddenLayer3],
'output': outputLayer
})
