问Maskrcnn : add_loss( )引发ValueError

EN

loss_names = [
        "rpn_class_loss",  "rpn_bbox_loss",
        "mrcnn_class_loss", "mrcnn_bbox_loss", "mrcnn_mask_loss"]

for name in loss_names:

layer = model_for_pruning.get_layer(name)
if layer.output in model_for_pruning.losses:
    continue

loss = (tf.reduce_mean(input_tensor=layer.output, keepdims=True)
       *config.LOSS_WEIGHTS.get(name, 1.))
model_for_pruning.add_loss(loss)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-43-542261a0e37d> in <module>
      9     loss = (tf.reduce_mean(input_tensor=layer.output, keepdims=True)
     10            *config.LOSS_WEIGHTS.get(name, 1.))
---> 11     model_for_pruning.add_loss(loss)

~\.conda\envs\maskrcnn\lib\site-packages\tensorflow_core\python\keras\engine\base_layer.py in add_loss(self, losses, inputs)
   1079       for symbolic_loss in symbolic_losses:
   1080         if getattr(self, '_is_graph_network', False):
-> 1081           self._graph_network_add_loss(symbolic_loss)
   1082         else:
   1083           # Possible a loss was added in a Layer's `build`.

~\.conda\envs\maskrcnn\lib\site-packages\tensorflow_core\python\keras\engine\network.py in _graph_network_add_loss(self, symbolic_loss)
   1482     new_nodes.extend(add_loss_layer.inbound_nodes)
   1483     new_layers.append(add_loss_layer)
-> 1484     self._insert_layers(new_layers, new_nodes)
   1485 
   1486   def _graph_network_add_metric(self, value, aggregation, name):

~\.conda\envs\maskrcnn\lib\site-packages\tensorflow_core\python\keras\engine\network.py in _insert_layers(self, layers, relevant_nodes)
   1421       # are being relied on.
   1422       if i > 10000:
-> 1423         raise ValueError('Layers could not be added due to missing '
   1424                          'dependencies.')
   1425 

ValueError: Layers could not be added due to missing dependencies.