我的张量流版本是0.11.我希望在训练后保存图形或保存tensorflow可以加载的其他东西.
我/使用导出和导入MetaGraph
我已经阅读过这篇文章: Tensorflow:如何保存/恢复模型?
我的Save.py文件:
X = tf.placeholder("float", [None, 28, 28, 1], name='X')
Y = tf.placeholder("float", [None, 10], name='Y')
tf.train.Saver()
with tf.Session() as sess:
...run something ...
final_tensor = tf.nn.softmax(py_x, name='final_result')
tf.add_to_collection("final_tensor", final_tensor)
predict_op = tf.argmax(py_x, 1)
tf.add_to_collection("predict_op", predict_op)
saver.save(sess, 'my_project')
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然后我运行load.py:
with tf.Session() as sess:
new_saver = tf.train.import_meta_graph('my_project.meta')
new_saver.restore(sess, 'my_project')
predict_op = tf.get_collection("predict_op")[0]
for i in range(2):
test_indices = np.arange(len(teX)) # Get A Test Batch
np.random.shuffle(test_indices)
test_indices = test_indices[0:test_size]
print(i, np.mean(np.argmax(teY[test_indices], axis=1) ==
sess.run(predict_op, feed_dict={"X:0": teX[test_indices],
"p_keep_conv:0": …Run Code Online (Sandbox Code Playgroud) python machine-learning neural-network deep-learning tensorflow