import random
from torchhk.rm import RecordManager
rm = RecordManager(['Epoch', 'Iter', 'loss_a', 'loss_b', 'train_acc', 'test_acc'])
rm
RecordManager(keys=[Epoch, Iter, loss_a, loss_b, train_acc, test_acc])
for epoch in range(5):
for i in range(2) :
#########
# Train #
#########
rm.progress()
rm.add([epoch+1, i,
random.random(), random.random(),
90+random.random()*(epoch+1), 90+random.random()*(epoch+1)])
rm.summary()
--------------------------------------------------------
Epoch Iter loss_a loss_b train_acc test_acc
========================================================
1 0 0.5122 0.8280 90.1486 90.2941
--------------------------------------------------------
1 1 0.1822 0.4356 90.1765 90.3528
--------------------------------------------------------
2 0 0.6448 0.4194 91.9486 90.3231
--------------------------------------------------------
2 1 0.8943 0.9038 91.0642 91.4241
--------------------------------------------------------
3 0 0.6358 0.7359 92.4341 90.5188
--------------------------------------------------------
3 1 0.9082 0.7852 92.3704 92.4229
--------------------------------------------------------
4 0 0.9486 0.1586 93.7000 91.9010
--------------------------------------------------------
4 1 0.9043 0.4352 90.6886 92.4582
--------------------------------------------------------
5 0 0.1235 0.1660 91.9936 91.1863
--------------------------------------------------------
5 1 0.6256 0.3831 91.1582 91.0011
--------------------------------------------------------
========================================================
Total Epoch: 5
Time Elapsed: 0:00:00.046384
Min(epoch)/Max(epoch):
-loss_a: 0.1235(5)/0.9486(4)
-loss_b: 0.1586(4)/0.9038(2)
-train_acc: 90.1486(1)/93.7000(4)
-test_acc: 90.2941(1)/92.4582(4)
--------------------------------------------------------
rm.plot('Epoch', 'loss_a')
rm.plot('Epoch', [['loss_a', 'loss_b'], ['train_acc', 'test_acc']],
title="All Records", xlabel='epochs', ylabel="loss", ylabel_second="acc",
ylim_second=(90,95),
linestyles=['-', '-', '--', '--'],
colors=['r', 'g', 'b', 'y'])