def train(self, qiju):
'''训练函数'''
sgf = SGFflie()
_x, _y = sgf.createTraindataFromqipu(qiju)
for i in range(10):
self.sess.run(self.train_step, feed_dict={self.x: _x, self.y: _y})
self.restore_save(method=0)
for row in qiju:
for point in row:
if point == -1:
tmp.append(0.0)
elif point == 0:
tmp.append(2.0)
elif point == 1:
tmp.append(1.0)
data.append(tmp)
return data
if __name__ == '__main__':
_cnn = myCNN()
path = sgf.allFileFromDir('.\\sgf\\')
_x, _y = sgf.createTraindataFromqipu(path[0])
step = 0
_path = path[:2000]
for i in range(10):
for filepath in path:
x, y = sgf.createTraindataFromqipu(filepath)
for i in range(10):
_cnn.sess.run(_cnn.train_step,
feed_dict={
_cnn.x: x,
_cnn.y: y,
_cnn.keep_prob: 0.5
})
print(step)
step += 1