本文整理汇总了Python中network.Network.forward_propagation方法的典型用法代码示例。如果您正苦于以下问题：Python Network.forward_propagation方法的具体用法？Python Network.forward_propagation怎么用？Python Network.forward_propagation使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类network.Network的用法示例。
在下文中一共展示了Network.forward_propagation方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: Network
# 需要导入模块: from network import Network [as 别名]
# 或者: from network.Network import forward_propagation [as 别名]
# train & test size
train_size = 1197
test_size = 1797 - train_size
# train
epoch = 100
nn = Network([64, 100, 10])
for e in xrange(epoch):
print u"epoch:%d" % e
for i in xrange(train_size):
nn.train(data[i], target[i])
#"""
correct = 0
for i in xrange(test_size):
output = nn.forward_propagation(data[i + train_size])
if np.argmax(output) == np.argmax(target[i + train_size]):
correct += 1
print u"correct: %d / %d" % (correct, test_size)
#"""
# test
correct = 0
for i in xrange(test_size):
output = nn.forward_propagation(data[i + train_size])
#print u"o:%d t:%d" % (np.argmax(output), np.argmax(target[i]))
if np.argmax(output) == np.argmax(target[i + train_size]):
correct += 1
else:
print u"error: %d & %d" % (np.argmax(output), np.argmax(target[i + train_size]))
print u"correct: %d / %d" % (correct, test_size)示例2: Network
# 需要导入模块: from network import Network [as 别名]
# 或者: from network.Network import forward_propagation [as 别名]
train_size = 50000
valid_size = 10000
test_size = 10000
# train
epoch = 100
nn = Network([784, 1500, 700, 10])
for e in xrange(epoch):
print "epoch:%d" % e
for i in xrange(train_size):
nn.train(train_data[i], train_target[i])
#"""
correct = 0
for i in xrange(test_size):
output = nn.forward_propagation(test_data[i])
if np.argmax(output) == np.argmax(test_target[i]):
correct += 1
print u"correct: %d / %d" % (correct, test_size)
#"""
# test
correct = 0
for i in xrange(test_size):
output = nn.forward_propagation(test_data[i])
if np.argmax(output) == np.argmax(test_target[i]):
correct += 1
else:
print u"error: %d & %d" % (np.argmax(output),
np.argmax(test_target[i]))
print u"correct: %d / %d" % (correct, test_size)