Tensorflow 2.1 / Keras - ошибка «output_node is not in graph» при попытке заморозить граф

Question

Я пытаюсь сохранить модель, которую создал, используя Keras, и сохранить как файл .h5, но я получаю это сообщение об ошибке каждый раз, когда пытаюсь запустить функцию freeze_session: output_node / Identity отсутствует в графике

Это мой код (я использую 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)

Который печатает:

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'] как положено (те же имена слоев и выводит, как в модели, которую я сохранил после тренировки).

Затем я пытаюсь вызвать функцию freeze_session и сохранить полученный замороженный график:

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)

, но я получаю эту ошибку:

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** 

Я пытался, но я не знаю, как это исправить, поэтому любая помощь будет высоко ценится.