windows下tensorflow兩種加載模型的測試數據方法

一、加載多次保存的模型中的某一次模型，而不是latest的一次

global sess

global charcnn

def get_logits_with_value_by_input(start,end):

    x=test_x[start:end]

    global sess

    global charcnn

    logits = sess.run(charcnn.predictions, feed_dict={charcnn.input_x: x, charcnn.dropout_keep_prob: 1})

    real_labels=test_y[start:end]

    real_labels_label=tf.argmax(real_labels,axis=1)

    return logits,real_labels_label

with tf.Graph().as_default():

    session_config=tf.ConfigProto(allow_soft_placement=True,log_device_placement=False)

    sess=tf.Session(config=session_config)

    with tf.Session() as sess:

        charcnn = charCNN(config.l0, config.num_classes, config.model.conv_layers, config.model.fc_layers,

                          l2_reg_lambda=0.0)

        saver = tf.train.Saver()

        #checkpoint_dir = os.path.abspath(os.path.join(out_dir, 'checkpoints'))

        if os.path.exists("./run/1513350504/checkpoints/checkpoint"):    #一定要用‘/’這個反斜槓

            print("Restoring Variables from Checkpoint")

            saver = tf.train.import_meta_graph('./run/1513350504/checkpoints/model-1200.meta')            #導入驗證準確率比較高的某個計算圖

            saver.restore(sess,'./run/1513350504/checkpoints/model-1200')                                                #加載模型，不加後綴名              

        else:

            print("Can't find the checkpoint.going to stop")

        logits,real_labels_label=get_logits_with_value_by_input(0,-1)

        print (logits)

        print (real_labels_label.eval())

二、直接加載checkpoint中最近latest的模型，（不過有時候模型收斂的不好，latest的模型準確率不高）

with tf.Graph().as_default():

    session_config=tf.ConfigProto(allow_soft_placement=True,log_device_placement=False)

    sess=tf.Session(config=session_config)

    with tf.Session() as sess:

        charcnn = charCNN(config.l0, config.num_classes, config.model.conv_layers, config.model.fc_layers,

                          l2_reg_lambda=0.0)

        saver = tf.train.Saver()

        #checkpoint_dir = os.path.abspath(os.path.join(out_dir, 'checkpoints'))

        if os.path.exists("checkpoint"):

            print("Restoring Variables from Checkpoint")

            saver.restore(sess, tf.train.latest_checkpoint('checkpoints/'))            #還是這種反斜槓

        else:

            print("Can't find the checkpoint.going to stop")

        logits,real_labels_label=get_logits_with_value_by_input(0,-1)

        print (logits)

        print (real_labels_label.eval())