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import mnist_loader

import Network as network

import numpy as np

import sys # for input argument from user

if __name__ == '__main__':

training_data, validation_data, test_data = mnist_loader.load_data_wrapper()

layers = [784]

for x in sys.argv[1:]:

layers.append(int(x))

layers.append(10)

print 'Given Layers as '

print layers

net = network.Network(layers)

net.SGD(training_data, 300, 10, 3.0, test_data = test_data)

# to save weights and biases to file

fname = "bw"

for l in layers:

fname = fname+'.'+str(l)

f = open(fname+'.bin','wb')

np.save(f,net.biases)

np.save(f,net.weights)

f.close()

#'''