def initialize_network(n_inputs, hidden_list, n_outputs):
	network = list()
	hidden_layer = [{'weights': [random() for i in range(n_inputs + 1)]} for i in range(hidden_list[0])]
	network.append(hidden_layer)
	for h in range(len(hidden_list) - 1):
		# print("h:",h)
		hidden_layer = [{'weights': [random() for i in range(hidden_list[h] + 1)]} for i in range(hidden_list[h + 1])]
		network.append(hidden_layer)

	output_layer = [{'weights': [random() for i in range(hidden_list[-1] + 1)]} for i in range(n_outputs)]
	network.append(output_layer)
	for layer in network:
		print("\nlayer no:", network.index(layer))
		for neuron in layer:
			print("neuron no:", layer.index(neuron))
			print(neuron)
	return network