diff --git a/AlphaGo/.gitignore b/AlphaGo/.gitignore
new file mode 100644
index 0000000..9ba06a7
--- /dev/null
+++ b/AlphaGo/.gitignore
@@ -0,0 +1,2 @@
+data
+checkpoints
diff --git a/AlphaGo/Network.py b/AlphaGo/Network.py
index d069927..be979f5 100644
--- a/AlphaGo/Network.py
+++ b/AlphaGo/Network.py
@@ -1,14 +1,16 @@
 import os
 import time
+import sys
 
 import numpy as np
 import tensorflow as tf
 import tensorflow.contrib.layers as layers
 
 import multi_gpu
+import time
 
-os.environ["CUDA_VISIBLE_DEVICES"] = "1"
-
+#os.environ["CUDA_VISIBLE_DEVICES"] = "1"
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
 
 def residual_block(input, is_training):
 	normalizer_params = {'is_training': is_training,
@@ -127,34 +129,46 @@ def train():
 						saver.save(sess, result_path + save_path)
 				del data, boards, wins, ps
 
+def forward(call_number):
+    #checkpoint_path = "/home/yama/rl/tianshou/AlphaGo/checkpoints"
+    checkpoint_path = "/home/yama/rl/tianshou/AlphaGo/checkpoints/jialian"
+    board_file = np.genfromtxt("/home/yama/rl/tianshou/leela-zero/src/mcts_nn_files/board_" + call_number, dtype='str');
+    human_board = np.zeros((17, 19, 19))
+    #TODO : is it ok to ignore the last channel?
+    for i in range(17):
+        human_board[i] = np.array(list(board_file[i])).reshape(19, 19)
+    feed_board = human_board.transpose(1, 2, 0).reshape(1, 19, 19, 17)
+    #print(feed_board.shape)
 
-def forward(board):
-	result_path = "./results/"
-	itflag = False
-	res = None
-	if board is None:
-		board = np.load("/home/yama/tongzheng/AG/self_play_204/d7d7d552b7be4b51883de99d74a8e51b.npz")
-		board = board["boards"][100].reshape(-1, 19, 19, 17)
-		result_path = "../parameters/checkpoints"
-		itflag = True
-	with multi_gpu.create_session() as sess:
-		sess.run(tf.global_variables_initializer())
-		ckpt_file = tf.train.latest_checkpoint(result_path)
-		if ckpt_file is not None:
-			print('Restoring model from {}...'.format(ckpt_file))
-			saver.restore(sess, ckpt_file)
-		else:
-			raise ValueError("No model loaded")
-		res = sess.run([tf.nn.softmax(p), v], feed_dict={x: board, is_training: itflag})
-		# res = sess.run([tf.nn.softmax(p),v], feed_dict={x:fix_board["boards"][300].reshape(-1, 19, 19, 17), is_training:False})
-		# res = sess.run([tf.nn.softmax(p),v], feed_dict={x:fix_board["boards"][50].reshape(-1, 19, 19, 17), is_training:True})
-		print(res)
-	# print(res[0].tolist()[0])
-	# print(np.argmax(res[0]))
-	return res
+    #npz_board = np.load("/home/yama/rl/tianshou/AlphaGo/data/7f83928932f64a79bc1efdea268698ae.npz")
+    #print(npz_board["boards"].shape)
+    #feed_board = npz_board["boards"][10].reshape(-1, 19, 19, 17)
+    ##print(feed_board)
+    #show_board = feed_board[0].transpose(2, 0, 1)
+    #print("board shape : ", show_board.shape)
+    #print(show_board)
 
+    itflag = True
+    with multi_gpu.create_session() as sess:
+            sess.run(tf.global_variables_initializer())
+            ckpt_file = tf.train.latest_checkpoint(checkpoint_path)
+            if ckpt_file is not None:
+            	#print('Restoring model from {}...'.format(ckpt_file))
+            	saver.restore(sess, ckpt_file)
+            else:
+            	raise ValueError("No model loaded")
+            res = sess.run([tf.nn.softmax(p),v], feed_dict={x:feed_board, is_training:itflag})
+            #res = sess.run([tf.nn.softmax(p),v], feed_dict={x:fix_board["boards"][300].reshape(-1, 19, 19, 17), is_training:False})
+            #res = sess.run([tf.nn.softmax(p),v], feed_dict={x:fix_board["boards"][50].reshape(-1, 19, 19, 17), is_training:True})
+            #print(np.argmax(res[0]))
+            np.savetxt(sys.stdout, res[0][0], fmt="%.6f", newline=" ")
+            np.savetxt(sys.stdout, res[1][0], fmt="%.6f", newline=" ")
+            pv_file = "/home/yama/rl/tianshou/leela-zero/src/mcts_nn_files/policy_value"
+            np.savetxt(pv_file, np.concatenate((res[0][0], res[1][0])), fmt="%.6f", newline=" ")
+            #np.savetxt(pv_file, res[1][0], fmt="%.6f", newline=" ")
+    return res
 
-if __name__ == '__main__':
-	train()
-# if sys.argv[1] == "test":
-#	forward(None)
+if __name__=='__main__':
+        np.set_printoptions(threshold='nan')
+        #time.sleep(2)
+        forward(sys.argv[1])