【发布时间】：2019-03-11 23:13:50
【问题描述】：
特意保存这里实现的整个MaskRCNN模型 https://github.com/matterport/Mask_RCNN
https://github.com/matterport/Mask_RCNN/blob/master/mrcnn/model.py 的第 2343 行基本上将 save_weights_only 从 True 更改为 False，以便保存整个模型。
keras.callbacks.ModelCheckpoint(self.checkpoint_path, verbose=0, save_weights_only=False),
错误的堆栈跟踪如下
File "./samples/coco/coco.py", line 509, in <module>
augmentation=augmentation)
File "/mask_rcnn_root/Mask_RCNN/mrcnn/model.py", line 2374, in train
use_multiprocessing=True,
File "/usr/local/lib/python3.5/dist-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/training.py", line 1415, in fit_generator
initial_epoch=initial_epoch)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/training_generator.py", line 247, in fit_generator
callbacks.on_epoch_end(epoch, epoch_logs)
File "/usr/local/lib/python3.5/dist-packages/keras/callbacks.py", line 77, in on_epoch_end
callback.on_epoch_end(epoch, logs)
File "/usr/local/lib/python3.5/dist-packages/keras/callbacks.py", line 455, in on_epoch_end
self.model.save(filepath, overwrite=True)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/network.py", line 1085, in save
save_model(self, filepath, overwrite, include_optimizer)
File "/usr/local/lib/python3.5/dist-packages/keras/engine/saving.py", line 116, in save_model
'config': model.get_config()
File "/usr/local/lib/python3.5/dist-packages/keras/engine/network.py", line 926, in get_config
return copy.deepcopy(config)
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 218, in _deepcopy_list
y.append(deepcopy(a, memo))
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 223, in _deepcopy_tuple
y = [deepcopy(a, memo) for a in x]
File "/usr/lib/python3.5/copy.py", line 223, in <listcomp>
y = [deepcopy(a, memo) for a in x]
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 223, in _deepcopy_tuple
y = [deepcopy(a, memo) for a in x]
File "/usr/lib/python3.5/copy.py", line 223, in <listcomp>
y = [deepcopy(a, memo) for a in x]
File "/usr/lib/python3.5/copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python3.5/copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python3.5/copy.py", line 182, in deepcopy
y = _reconstruct(x, rv, 1, memo)
File "/usr/lib/python3.5/copy.py", line 297, in _reconstruct
state = deepcopy(state, memo)
File "/usr/lib/python3.5/copy.py", line 155, in deepcopy
y = copier(x, memo)
File "/usr/lib/python3.5/copy.py", line 243, in _deepcopy_dict
y[deepcopy(key, memo)] = deepcopy(value, memo)
File "/usr/lib/python3.5/copy.py", line 174, in deepcopy
rv = reductor(4)
TypeError: can't pickle SwigPyObject objects keras
谢谢！
【问题讨论】：
-
在使用回调保存模型检查点时，我也陷入了困境。解决了吗？
-
@jessietio 我发现在这种情况下，原因是 Lambda 层与 Keras 的使用不当导致模型无法保存。不过，您仍然可以节省重量。
-
我发现了同样的事情。我已经将 lambda 层变成了自定义层。
标签： python python-3.x tensorflow keras