Running multiple Nengo models using python multiprocessing

I am running multiple nengo models using python multiprocessing library and I got following user warning

nengo/ UserWarning: Decoder cache index could not acquire lock. Cache index was not synced.

Could will it cause any complications sooner or later?

No, that should be fine (it just means that you won’t benefit from the caching). But you could add nengo.rc.set("decoder_cache", "enabled", False) if you want to explicitly disable the cache and avoid those warnings.

1 Like

Found this thread while googling for documentation. You’ll want to use:

nengo.rc.set("decoder_cache", "enabled", "False")

("False" instead of False) otherwise you’ll get:

TypeError                                 Traceback (most recent call last)
<ipython-input-2-4005b404c25d> in <module>
      1 import nengo
----> 2 nengo.rc.set("decoder_cache", "enabled", False)

~/anaconda3/envs/py36/lib/python3.6/ in set(self, section, option, value)
   1190         """Set an option.  Extends RawConfigParser.set by validating type and
   1191         interpolation syntax on the value."""
-> 1192         self._validate_value_types(option=option, value=value)
   1193         super().set(section, option, value)

~/anaconda3/envs/py36/lib/python3.6/ in _validate_value_types(self, section, option, value)
   1175         if not self._allow_no_value or value:
   1176             if not isinstance(value, str):
-> 1177                 raise TypeError("option values must be strings")
   1179     @property

TypeError: option values must be strings