我的tensorflow版本是0.11。 我想在训练后保存一张图,或者保存其他东西让 tensorflow 可以加载它。
我/使用导出和导入元图
我已经读过这篇文章: Tensorflow: how to save/restore a model?
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')
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": 1.0,
"p_keep_hidden:0": 1.0})))
但它返回错误
Traceback (most recent call last):
File "load_05_convolution.py", line 62, in <module>
"p_keep_hidden:0": 1.0})))
File "/home/khoa/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 717, in run
run_metadata_ptr)
File "/home/khoa/tensorflow/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 894, in _run
% (np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (256, 784) for Tensor u'X:0', which has shape '(?, 28, 28, 1)'
我真的不知道为什么?
如果我添加 final_tensor = tf.get_collection("final_result")[0]
它返回另一个错误:
Traceback (most recent call last):
File "load_05_convolution.py", line 46, in <module>
final_tensor = tf.get_collection("final_result")[0]
IndexError: list index out of range
是因为 tf.add_to_collection 只包含一个占位符吗?
II/使用 tf.train.write_graph
我将这一行添加到 save.py 的末尾
tf.train.write_graph(graph, '文件夹', 'train.pb')
它成功地创建了文件'train.pb'
我的 load.py :
with tf.gfile.FastGFile('folder/train.pb', 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
_ = tf.import_graph_def(graph_def, name='')
with tf.Session() as sess:
predict_op = sess.graph.get_tensor_by_name('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": 1.0,
"p_keep_hidden:0": 1.0})))
然后返回错误:
Traceback (most recent call last):
File "load_05_convolution.py", line 22, in <module>
graph_def.ParseFromString(f.read())
File "/home/khoa/tensorflow/lib/python2.7/site-packages/google/protobuf/message.py", line 185, in ParseFromString
self.MergeFromString(serialized)
File "/home/khoa/tensorflow/lib/python2.7/site-packages/google/protobuf/internal/python_message.py", line 1085, in MergeFromString
raise message_mod.DecodeError('Unexpected end-group tag.')
google.protobuf.message.DecodeError: Unexpected end-group tag.
您介意分享保存/加载模型的标准方法、代码或教程吗?我真的很困惑。
最佳答案
您的第一个解决方案(使用 MetaGraph)几乎可以工作,但出现错误是因为您将一批扁平化 MNIST 训练示例提供给 tf.placeholder()
期望一批 MNIST 训练示例作为形状为 batch_size
x height
(= 28) x width
(= 28) 的 4-D 张量x channel
(= 1)。解决此问题的最简单方法是 reshape 输入数据。而不是这个声明:
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": 1.0,
"p_keep_hidden:0": 1.0})))
...请尝试以下语句,它会适本地 reshape 您的输入数据:
print(i, np.mean(np.argmax(teY[test_indices], axis=1) ==
sess.run(predict_op, feed_dict={
"X:0": teX[test_indices].reshape(-1, 28, 28, 1),
"p_keep_conv:0": 1.0,
"p_keep_hidden:0": 1.0})))
关于python - 在 tensorflow 中训练后如何使用模型(保存/加载图表),我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/40956040/