我已经定义、训练并保存了我的张量 keras NN。既然已经完成了，我如何使用它将分类输出到非训练数据？

import tensorflow as tf
import numpy as np
from tensorflow.keras import layers
from syslog import syslog_pred

model = tf.keras.Sequential()
# Adds a densely-connected layer with 64 units to the model:
model.add(layers.Dense(128, activation='relu'))
# Add another:
model.add(layers.Dense(128, activation='relu'))
# Add a softmax layer with 8 output units:
model.add(layers.Dense(8, activation='softmax'))

model.compile(optimizer=tf.train.AdamOptimizer(0.001),
              loss='categorical_crossentropy',
              metrics=['accuracy'])

model.load_weights('.my_model')

x = np.array([arr[:-1] for arr in syslog_pred], dtype=np.float32)
dataset = tf.data.Dataset.from_tensor_slices(x)

answer = model.predict(dataset, steps=30)
print(answer)

最后的代码不是应该的，但我有点迷茫。任何帮助，将不胜感激！