我正在尝试保存使用 Keras 创建的模型并保存为 .h5 文件，但每次尝试运行 freeze_session 函数时都会收到此错误消息：输出节点/身份不在图中
这是我的代码（我使用的是 Tensorflow 2.1.0）：
def freeze_session(session, keep_var_names=None, output_names=None, clear_devices=True):
"""
Freezes the state of a session into a pruned computation graph.
Creates a new computation graph where variable nodes are replaced by
constants taking their current value in the session. The new graph will be
pruned so subgraphs that are not necessary to compute the requested
outputs are removed.
@param session The TensorFlow session to be frozen.
@param keep_var_names A list of variable names that should not be frozen,
or None to freeze all the variables in the graph.
@param output_names Names of the relevant graph outputs.
@param clear_devices Remove the device directives from the graph for better portability.
@return The frozen graph definition.
"""
graph = session.graph
with graph.as_default():
freeze_var_names = list(set(v.op.name for v in tf.compat.v1.global_variables()).difference(keep_var_names or []))
output_names = output_names or []
output_names += [v.op.name for v in tf.compat.v1.global_variables()]
input_graph_def = graph.as_graph_def()
if clear_devices:
for node in input_graph_def.node:
node.device = ""
frozen_graph = tf.compat.v1.graph_util.convert_variables_to_constants(
session, input_graph_def, output_names, freeze_var_names)
return frozen_graph
model=kr.models.load_model("model.h5")
model.summary()
# inputs:
print('inputs: ', model.input.op.name)
# outputs:
print('outputs: ', model.output.op.name)
#layers:
layer_names=[layer.name for layer in model.layers]
print(layer_names)
哪个打印：
inputs: input_node
outputs: output_node/Identity
['input_node', 'conv2d_6', 'max_pooling2d_6', 'conv2d_7', 'max_pooling2d_7', 'conv2d_8', 'max_pooling2d_8', 'flatten_2', 'dense_4', 'dense_5', 'output_node']
正如预期的那样（与我在训练后保存的模型中相同的层名称和输出）。
然后我尝试调用 freeze_session 函数并保存生成的冻结图：
frozen_graph = freeze_session(K.get_session(), output_names=[out.op.name for out in model.outputs])
write_graph(frozen_graph, './', 'graph.pbtxt', as_text=True)
write_graph(frozen_graph, './', 'graph.pb', as_text=False)
但我收到此错误：
AssertionError Traceback (most recent call last)
<ipython-input-4-1848000e99b7> in <module>
----> 1 frozen_graph = freeze_session(K.get_session(), output_names=[out.op.name for out in model.outputs])
2 write_graph(frozen_graph, './', 'graph.pbtxt', as_text=True)
3 write_graph(frozen_graph, './', 'graph.pb', as_text=False)
<ipython-input-2-3214992381a9> in freeze_session(session, keep_var_names, output_names, clear_devices)
24 node.device = ""
25 frozen_graph = tf.compat.v1.graph_util.convert_variables_to_constants(
---> 26 session, input_graph_def, output_names, freeze_var_names)
27 return frozen_graph
c:\users\marco\anaconda3\envs\tfv2\lib\site-packages\tensorflow_core\python\util\deprecation.py in new_func(*args, **kwargs)
322 'in a future version' if date is None else ('after %s' % date),
323 instructions)
--> 324 return func(*args, **kwargs)
325 return tf_decorator.make_decorator(
326 func, new_func, 'deprecated',
c:\users\marco\anaconda3\envs\tfv2\lib\site-packages\tensorflow_core\python\framework\graph_util_impl.py in convert_variables_to_constants(sess, input_graph_def, output_node_names, variable_names_whitelist, variable_names_blacklist)
275 # This graph only includes the nodes needed to evaluate the output nodes, and
276 # removes unneeded nodes like those involved in saving and assignment.
--> 277 inference_graph = extract_sub_graph(input_graph_def, output_node_names)
278
279 # Identify the ops in the graph.
c:\users\marco\anaconda3\envs\tfv2\lib\site-packages\tensorflow_core\python\util\deprecation.py in new_func(*args, **kwargs)
322 'in a future version' if date is None else ('after %s' % date),
323 instructions)
--> 324 return func(*args, **kwargs)
325 return tf_decorator.make_decorator(
326 func, new_func, 'deprecated',
c:\users\marco\anaconda3\envs\tfv2\lib\site-packages\tensorflow_core\python\framework\graph_util_impl.py in extract_sub_graph(graph_def, dest_nodes)
195 name_to_input_name, name_to_node, name_to_seq_num = _extract_graph_summary(
196 graph_def)
--> 197 _assert_nodes_are_present(name_to_node, dest_nodes)
198
199 nodes_to_keep = _bfs_for_reachable_nodes(dest_nodes, name_to_input_name)
c:\users\marco\anaconda3\envs\tfv2\lib\site-packages\tensorflow_core\python\framework\graph_util_impl.py in _assert_nodes_are_present(name_to_node, nodes)
150 """Assert that nodes are present in the graph."""
151 for d in nodes:
--> 152 assert d in name_to_node, "%s is not in graph" % d
153
154
**AssertionError: output_node/Identity is not in graph**
我已经尝试过，但我真的不知道如何解决这个问题，所以任何帮助将不胜感激。
