"InpNet2 err: {:4.4f}".format(inp_net_2.train(inp, tgt_2, 1)[0]))
metanet = MetaNet()
metanet.add_input_net(inp_net_1)
metanet.add_input_net(inp_net_2)
metanet.add_output_net(out_net)
metanet.connect_nets(inp_net_1, out_net)
metanet.connect_nets(inp_net_2, out_net)
metanet.connect_nets(out_net, inp_net_1)
metanet.connect_nets(out_net, inp_net_2)
metanet.name = 'MetaNet'
metanet.add_action_on_active(lambda x: print(x.get_name(), 'activation found'),
lambda net: net.get_out_state()[0][0] > 0.4)
inp_net_1.add_action_on_active(lambda x: print(x.get_name(),
'net has ',
x.get_layer_state(0)[0],
'on input fist neuron'),
lambda net: net.get_layer_state(0)[0] > 0.4)
print("\nIntNet1 input = [1.0, 0.0], InpNet2 input = [0.0, 0.0]")
print('-'*10)
print("OutNet output = {:4.4f}".format(metanet.test([[1.0, 0.0], [0.0, 0.0]])[0][0]))
print("Must be -> 0.0")
#metanet.draw_metanet()
#out_net.draw_net()
