import mnist_loader
import network
import time as time

training_data, validation_data, test_data =  mnist_loader.load_data_wrapper()

t0 = time.time()

net = network.Network([784, 30, 10])
net.SGD(training_data, 10, 3, 3.0, validation_data)
print("Training time: %.2f" % (time.time()-t0))
print("Testing set accuracy: %.2f%%" % (net.evaluate(test_data)/100.0))







5b8dd1e581ddf0e4ea326a53ba27c7fe70b4a04d
<mask token>

<mask token>
net.SGD(training_data, 10, 3, 3.0, validation_data)
print('Training time: %.2f' % (time.time() - t0))
print('Testing set accuracy: %.2f%%' % (net.evaluate(test_data) / 100.0))

<mask token>
training_data, validation_data, test_data = mnist_loader.load_data_wrapper()
t0 = time.time()
net = network.Network([784, 30, 10])
net.SGD(training_data, 10, 3, 3.0, validation_data)
print('Training time: %.2f' % (time.time() - t0))
print('Testing set accuracy: %.2f%%' % (net.evaluate(test_data) / 100.0))

import mnist_loader
import network
import time as time
training_data, validation_data, test_data = mnist_loader.load_data_wrapper()
t0 = time.time()
net = network.Network([784, 30, 10])
net.SGD(training_data, 10, 3, 3.0, validation_data)
print('Training time: %.2f' % (time.time() - t0))
print('Testing set accuracy: %.2f%%' % (net.evaluate(test_data) / 100.0))

import mnist_loader
import network
import time as time

training_data, validation_data, test_data =  mnist_loader.load_data_wrapper()

t0 = time.time()

net = network.Network([784, 30, 10])
net.SGD(training_data, 10, 3, 3.0, validation_data)
print("Training time: %.2f" % (time.time()-t0))
print("Testing set accuracy: %.2f%%" % (net.evaluate(test_data)/100.0))






