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