network.py 文件源码

def __init__(self, image_size=24, num_classes=10, batch_size=50, channels=3):
        self._image_size = image_size
        self._num_classes = num_classes
        self._batch_size = batch_size
        self._channels = channels
        gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.333)
        self._session = tf.Session(config=tf.ConfigProto(gpu_options=gpu_options))
        self._images = tf.placeholder(tf.float32, shape=[None, self._image_size, self._image_size, self._channels])
        self._labels = tf.placeholder(tf.int64, shape=[None])
        self._keep_prob = tf.placeholder(tf.float32)
        self._global_step = tf.Variable(0, tf.int64, name="global_step") 
        self._logits = self._inference(self._images, self._keep_prob)
        self._avg_loss = self._loss(self._labels, self._logits)
        self._train_op = self._train(self._avg_loss)
        self._accuracy = F.accuracy_score(self._labels, self._logits)
        self._saver = tf.train.Saver(tf.all_variables())
        self._session.run(tf.initialize_all_variables())