from unittest import TestCase
from metanet.networks.artificial_networks.feedforward_network import FeedforwardNetwork
from metanet.networks.metanet import MetaNet
from metanet.datasets.xor import get_xor
import networkx as nx
#import matplotlib.pyplot as plt
if __name__=='__main__':
inp, tgt = get_xor()
out_net = FeedforwardNetwork(2, [4], 2)
inp_net_1 = FeedforwardNetwork(2, [4], 2)
inp_net_2 = FeedforwardNetwork(2, [4], 2)
out_net.name = 'out'
inp_net_1.name = 'inp1'
inp_net_2.name = 'inp2'
tgt_1 = [[0.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]]
tgt_2 = [[0.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 0.0]]
for i in range(500):
print("OutNet err: {:4.4f}".format(out_net.train(inp, tgt_1, 1)[0]),
"InpNet1 err: {:4.4f}".format(inp_net_1.train(inp, tgt_1, 1)[0]),
"InpNet2 err: {:4.4f}".format(inp_net_2.train(inp, tgt_2, 1)[0]))
metanet = MetaNet()
from unittest import TestCase
from metanet.networks.artificial_networks.feedforward_network import FeedforwardNetwork
from metanet.networks.metanet import MetaNet
from metanet.datasets.xor import get_xor
if __name__=='__main__':
inp, tgt = get_xor()
out_net = FeedforwardNetwork(2, [4], 1)
inp_net_1 = FeedforwardNetwork(2, [4], 2)
inp_net_2 = FeedforwardNetwork(2, [4], 2)
tgt_1 = [[0.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]]
tgt_2 = [[0.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 0.0]]
for i in range(500):
print("OutNet err: {:4.4f}".format(out_net.train(inp, tgt, 1)[0]),
"InpNet1 err: {:4.4f}".format(inp_net_1.train(inp, tgt_1, 1)[0]),
"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)
from unittest import TestCase
from metanet.networks.artificial_networks.feedforward_network import FeedforwardNetwork
from metanet.networks.metanet import MetaNet
from metanet.datasets.xor import get_xor
import networkx as nx
if __name__=='__main__':
inp, tgt = get_xor()
out_net = FeedforwardNetwork(2, [4], 2)
inp_net_1 = FeedforwardNetwork(2, [4], 2)
inp_net_2 = FeedforwardNetwork(2, [4], 2)
out_net.name = 'out'
inp_net_1.name = 'inp1'
inp_net_2.name = 'inp2'
tgt_1 = [[0.0, 0.0], [1.0, 0.0], [1.0, 0.0], [0.0, 0.0]]
tgt_2 = [[0.0, 0.0], [0.0, 1.0], [0.0, 1.0], [0.0, 0.0]]
for i in range(500):
print("OutNet err: {:4.4f}".format(out_net.train(inp, tgt_1, 1)[0]),
"InpNet1 err: {:4.4f}".format(inp_net_1.train(inp, tgt_1, 1)[0]),
"InpNet2 err: {:4.4f}".format(inp_net_2.train(inp, tgt_2, 1)[0]))
metanet = MetaNet()
metanet.add_input_net(inp_net_1)
"""
__author__ = "Evtushenko Georgy"
from metanet.networks.artificial_networks.feedforward_network import FeedforwardNetwork
from metanet.datasets import mnist
import argparse
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-t", "--train", default="true")
args = parser.parse_args()
inp, tgt = mnist.get_mnist(10)
net = FeedforwardNetwork(len(inp[0]), [len(inp[0])], len(tgt[0]))
if args.train == "true":
for i in range(50):
print(" [*] Epoch:", i, "error:", net.train(inp, tgt, 1))
else:
net.load_net("./data/net.pkl")
err = 0
for i in range(len(tgt)):
ans = net.test(inp[i])
if tgt[i].index(max(tgt[i])) != ans.index(max(ans)):
err += 1
if args.train == "true":
from metanet.networks.artificial_networks.feedforward_network import FeedforwardNetwork from metanet.datasets.xor import get_xor inp, tgt = get_xor() net = FeedforwardNetwork(len(inp[0]), [4], len(tgt[0])) net.eta = 0.45 for i in range(10000): print(net.train(inp, tgt, 1)[0])
