import run_uct
import math
import run_algorithm
from graph_construction import graph
import matplotlib.pyplot as plt
mygraph = graph()
mytree = graph()
print(mygraph)
machine_number = 100
sample_number = 500
epsilon = 0.1
delta = 0.1
time_list = range(67, 1500, 1)
eta = 0.7
gamma = 1
a = 0.5 * (1 + eta) * math.log(4 * mygraph.leaf_node_number *
(1 + eta) / delta / (1 - eta))
cm = 1
cp = 1
a1 = run_algorithm.run_algorithm(mygraph, machine_number, sample_number,
epsilon, delta, time_list, eta, gamma, a,
'paper', cm)
a2 = run_uct.run_uct_new(mygraph, machine_number, sample_number, time_list,
eta, gamma, cp)
a3 = run_uct.run_uct_new(mytree, machine_number, sample_number, time_list, eta,
gamma, cp)
plt.plot(time_list, a1, label='P-MCG', lw=3)
plt.plot(time_list, a2, label='P-UCT(graph)', lw=3)
import run_uct
import math
import run_algorithm
from graph_construction import graph
import matplotlib.pyplot as plt
mygraph = graph()
print(mygraph)
machine_number = 300
sample_number = 500
epsilon = 0.1
delta = 0.1
time_list = range(300)
eta = 0.7
gamma = 1
a = 0.5 * (1 + eta) * math.log(4 * mygraph.leaf_node_number *
(1 + eta) / delta / (1 - eta))
cm = 1
cp = 1
a1 = run_algorithm.run_algorithm(mygraph, machine_number, sample_number,
epsilon, delta, time_list, eta, gamma, a,
'paper', cm)
a2 = run_uct.run_uct_new(mygraph, machine_number, sample_number, time_list,
eta, gamma, cp)
plt.plot(time_list, a1, label='P-MCGS', lw=3)
plt.plot(time_list, a2, label='P-UCT', lw=3)
plt.xlabel("iterations", size=21)
})
label = sess.run(labels,
feed_dict={
x: batch_tx,
y: batch_ty,
keep_prob: 1
})
print("labels={}".format(label))
test_acc += acc
test_count += 1
test_acc /= test_count
print("Validation score = {} {}".format(datetime.now(), test_acc))
'''
smoothness computation:
'''
val_num = len(val_label)
val_graph_index = val_index[:val_num]
construction_graph = graph(train_index, train_label, val_graph_index,
val_label)
smoothness = construction_graph.smoothness * 0.01
val_generator.reset_pointer()
train_generator.reset_pointer()
'''
print("{} Saving checkpoint of model...".format(datetime.now()))
checkpoint_name = os.path.join(
checkpoint_path, 'model_epoch' + str(epoch + 1) + '.ckpt')
save_path = saver.save(sess, checkpoint_name)
print("{} Model checkpoint saved at {}".format(datetime.now(),checkpoint_name))
'''
