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Update network.py #92

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26 changes: 13 additions & 13 deletions src/network.py
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Original file line number Diff line number Diff line change
Expand Up @@ -51,20 +51,20 @@ def SGD(self, training_data, epochs, mini_batch_size, eta,
network will be evaluated against the test data after each
epoch, and partial progress printed out. This is useful for
tracking progress, but slows things down substantially."""
if test_data: n_test = len(test_data)
n = len(training_data)
for j in xrange(epochs):
random.shuffle(training_data)
mini_batches = [
training_data[k:k+mini_batch_size]
for k in xrange(0, n, mini_batch_size)]
temp_test_data = copy.deepcopy(test_data)
test_data_list = list(temp_test_data)
n_test= len(test_data_list)

temp_training_data = copy.deepcopy(training_data)
training_data_list = list(temp_training_data)
n_training = len(training_data_list)

for j in range(epochs):
random.shuffle(training_data_list)
mini_batches = [training_data_list[k:k+mini_batch_size] for k in range(0, n_training, mini_batch_size)]
for mini_batch in mini_batches:
self.update_mini_batch(mini_batch, eta)
if test_data:
print "Epoch {0}: {1} / {2}".format(
j, self.evaluate(test_data), n_test)
else:
print "Epoch {0} complete".format(j)
self.update_mini_batch(mini_batch, mini_batch_size,eta)
print ("Epoch {0}: {1} / {2}".format(j, self.evaluate(test_data_list), n_test))

def update_mini_batch(self, mini_batch, eta):
"""Update the network's weights and biases by applying
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