diff --git a/AlphaGo/Network.py b/AlphaGo/Network.py
index f594be2..d350247 100644
--- a/AlphaGo/Network.py
+++ b/AlphaGo/Network.py
@@ -50,7 +50,7 @@ p = policy_heads(h, is_training)
 loss = tf.reduce_mean(tf.square(z-v)) - tf.reduce_mean(tf.multiply(pi, tf.log(tf.nn.softmax(p, 1))))
 reg = tf.add_n(tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES))
 total_loss = loss + reg
-train_op = tf.train.RMSPropOptimizer(1e-2).minimize(total_loss)
+train_op = tf.train.RMSPropOptimizer(1e-4).minimize(total_loss)
 
 var_list = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
 saver = tf.train.Saver(max_to_keep=10, var_list=var_list)
@@ -104,4 +104,7 @@ def forward(board):
 			saver.restore(sess, ckpt_file)
 		else:
 			raise ValueError("No model loaded")
-		return sess.run([p,v], feed_dict={x:board})
\ No newline at end of file
+		return sess.run([p,v], feed_dict={x:board})
+
+if __name__ == "__main__":
+	train()
\ No newline at end of file
diff --git a/AlphaGo/Network.pyc b/AlphaGo/Network.pyc
new file mode 100644
index 0000000..8691e53
Binary files /dev/null and b/AlphaGo/Network.pyc differ
diff --git a/AlphaGo/multi_gpu.pyc b/AlphaGo/multi_gpu.pyc
new file mode 100644
index 0000000..d269ca5
Binary files /dev/null and b/AlphaGo/multi_gpu.pyc differ