Tensorflow：查询SavedModel总是返回相同的结果

Question

这个问题困扰了一个星期，有人可以在这里找到问题吗？排除了其他部分的潜在错误。不管输入什么，查询SavedModel总是返回相同的结果。

    // x and y_ are from the tagged data, y is the output from Neural Network
    x = tf.placeholder(tf.float32,[None,300],name='x-input')
    y_ = tf.placeholder(tf.float32,[None,7],name='y-input')
    y = inference(x,regularizer,norm=True)
    # some codes are omitted here for simplicity

    // save the model
    export_path = './savedmodel'
    if tf.gfile.Exists(export_path):
        tf.gfile.DeleteRecursively(export_path)
    builder = tf.saved_model.builder.SavedModelBuilder(export_path)
    tensor_info_x = tf.saved_model.utils.build_tensor_info(x)
    tensor_info_y = tf.saved_model.utils.build_tensor_info(y)
    prediction_signature = (
          tf.saved_model.signature_def_utils.build_signature_def(
              inputs={'xx': tensor_info_x},
              outputs={'yy': tensor_info_y},
              method_name=tf.saved_model.signature_constants.PREDICT_METHOD_NAME))
    builder.add_meta_graph_and_variables(
          sess, [tf.saved_model.tag_constants.SERVING],
          signature_def_map={
              tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY:
                    prediction_signature
          })
    builder.save()

    // query the model
    sess=tf.Session()
    signature_key = tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY
    input_key = 'xx'
    output_key = 'yy'
    export_path = './savedmodel'
    meta_graph_def = tf.saved_model.loader.load(
        sess,
        [tf.saved_model.tag_constants.SERVING],
        export_path)
    signature = meta_graph_def.signature_def
    x_tensor_name = signature[signature_key].inputs[input_key].name
    y_tensor_name = signature[signature_key].outputs[output_key].name
    x = sess.graph.get_tensor_by_name(x_tensor_name)
    y = sess.graph.get_tensor_by_name(y_tensor_name)
    x1 = [[num1, num2, ..., num300]]
    print(sess.run(y, {x: x1}))