diff --git a/src/network.py b/src/network.py
index f66c362d4..652777b83 100644
--- a/src/network.py
+++ b/src/network.py
@@ -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