TypeError: unhashable type: 'ListWrapper' when try to train model

[littlepae]

Hello. Could you please help me figure out this error when i run this training command

for epochs, parameters in train_schedule.items():
    print("")
    print("training layers {} until epoch {} with learning_rate {}".format(parameters["layers"], 
                                                                          epochs, 
                                                                          parameters["learning_rate"]))
    model.train(coco_train, coco_val, 
                learning_rate=parameters["learning_rate"], 
                epochs=epochs, 
                layers=parameters["layers"])

After that. I got this following output and error

training layers heads until epoch 1 with learning_rate 0.02

Starting at epoch 0. LR=0.02

Checkpoint Path: C:\Users\supha\Desktop\FIBO\intern\Onboard\siamese-mask-rcnn-master - Copy\logs\siamese_mrcnn_small_coco_example\siamese_mrcnn_{epoch:04d}.h5
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Input In [11], in <cell line: 1>()
      2 print("")
      3 print("training layers {} until epoch {} with learning_rate {}".format(parameters["layers"], 
      4                                                                       epochs, 
      5                                                                       parameters["learning_rate"]))
----> 6 model.train(coco_train, coco_val, 
      7             learning_rate=parameters["learning_rate"], 
      8             epochs=epochs, 
      9             layers=parameters["layers"])

File ~\Desktop\FIBO\intern\Onboard\siamese-mask-rcnn-master - Copy\lib\model.py:711, in SiameseMaskRCNN.train(self, train_dataset, val_dataset, learning_rate, epochs, layers, augmentation)
    709 modellib.log("Checkpoint Path: {}".format(self.checkpoint_path))
    710 self.set_trainable(layers)
--> 711 self.compile(learning_rate, self.config.LEARNING_MOMENTUM)
    713 # Work-around for Windows: Keras fails on Windows when using
    714 # multiprocessing workers. See discussion here:
    715 # https://github.com/matterport/Mask_RCNN/issues/13#issuecomment-353124009
    716 if os.name is 'nt':

File ~\Desktop\FIBO\intern\Onboard\siamese-mask-rcnn-master - Copy\lib\model.py:540, in SiameseMaskRCNN.compile(self, learning_rate, momentum)
    538         continue
    539     loss = (tf.reduce_mean(input_tensor=layer.output, keepdims=True) * self.config.LOSS_WEIGHTS.get(name, 1.))
--> 540     self.keras_model.add_loss(loss)
    542 # Add L2 Regularization
    543 # Skip gamma and beta weights of batch normalization layers.
    544 reg_losses = [
    545     keras.regularizers.l2(self.config.WEIGHT_DECAY)(w) / tf.cast(tf.size(w), tf.float32)
    546     for w in self.keras_model.trainable_weights
    547     if 'gamma' not in w.name and 'beta' not in w.name]

File ~\Desktop\FIBO\intern\Onboard\.venv\lib\site-packages\keras\engine\base_layer_v1.py:1054, in Layer.add_loss(self, losses, inputs)
   1052 for symbolic_loss in symbolic_losses:
   1053   if getattr(self, '_is_graph_network', False):
-> 1054     self._graph_network_add_loss(symbolic_loss)
   1055   else:
   1056     # Possible a loss was added in a Layer's `build`.
   1057     self._losses.append(symbolic_loss)

File ~\Desktop\FIBO\intern\Onboard\.venv\lib\site-packages\keras\engine\functional.py:908, in Functional._graph_network_add_loss(self, symbolic_loss)
    906 new_nodes.extend(add_loss_layer.inbound_nodes)
    907 new_layers.append(add_loss_layer)
--> 908 self._insert_layers(new_layers, new_nodes)

File ~\Desktop\FIBO\intern\Onboard\.venv\lib\site-packages\keras\engine\functional.py:851, in Functional._insert_layers(self, layers, relevant_nodes)
    848     self._nodes_by_depth[depth].append(node)
    850 # Insert layers and update other layer attrs.
--> 851 layer_set = set(self._self_tracked_trackables)
    852 deferred_layers = []
    853 for layer in layers:

File ~\Desktop\FIBO\intern\Onboard\.venv\lib\site-packages\tensorflow\python\training\tracking\data_structures.py:668, in ListWrapper.__hash__(self)
    665 def __hash__(self):
    666   # List wrappers need to compare like regular lists, and so like regular
    667   # lists they don't belong in hash tables.
--> 668   raise TypeError("unhashable type: 'ListWrapper'")

TypeError: unhashable type: 'ListWrapper'

I run this code with tensorflow 2.5.0 and keras 2.8.0 and i tried to change something in loss function code but it's still same error
Thanks for help!

[michaelisc]

The project was built using Tensorflow 1 (I don't exactly remember which version) and Keras 2.1.6.