Open Oeyvind opened 10 years ago
After some googling, this could be an indication that you are running out of memory. Could you see what your memory usage is when having this many networks in the brain?
It seems correct that it is related to memory usage. Bigger brains crash on save, smaller ones not. Successful save done on brain files of approx 700MB. Overall (system wide) memory use at approx 4.5 GB Will test on 64 bit Python soon.
When trying to save a brain, I got this error.
[self.] received: save braintest Process Process-7: Traceback (most recent call last): File "C:\Python27\lib\multiprocessing\process.py", line 232, in _bootstrap self.run() File "C:\Python27\lib\multiprocessing\process.py", line 88, in run self._target(_self._args, *_self._kwargs) File "C:\Projects\self_dot\git\self_dot\IO.py", line 216, in cns pickle.dump(brain[:], file(state['save'], 'w')) File "", line 2, in getslice
File "C:\Python27\lib\multiprocessing\managers.py", line 747, in _callmethod
raise convert_to_error(kind, result)
RemoteError:
Unserializable message: ('#RETURN', [(FlowNode(input_dim=527, output_dim=None, dtype='float64'), <esn.ACDCESN instance at 0x067F0B48>, MinMaxScaler(co py=True, feature_range=(0, 1))), (FlowNode(input_dim=527, output_dim=None, dtype='float64'), <esn.ACDCESN instance at 0x032FDB20>, MinMaxScaler(copy=T rue, feature_range=(0, 1))), (FlowNode(input_dim=527, output_dim=None, dtype='float64'), <esn.ACDCESN instance at 0x035153A0>, MinMaxScaler(copy=True, feature_range=(0, 1))), (FlowNode(input_dim=527, output_dim=None, dtype='float64'), <esn.ACDCESN instance at 0x03513580>, MinMaxScaler(copy=True, fea ture_range=(0, 1))), (FlowNode(input_dim=527, output_dim=None, dtype='float64'), <esn.ACDCESN instance at 0x068076E8>, MinMaxScaler(copy=True, feature _range=(0, 1))), (FlowNode(input_dim=527, output_dim=None, dtype='float64'), <esn.ACDCESN instance at 0x067F8EB8>, MinMaxScaler(copy=True, feature_ran ge=(0, 1))), (FlowNode(input_dim=527, output_dim=None, dtype='float64'), <esn.ACDCESN instance at 0x067F8D28>, MinMaxScaler(copy=True, feature_range=(
0, 1)))])