Hello there!
I have a network that I intend to deploy on Loihi as well as make the Connection
s’ weights learnable through a rule specified in the NxSDK API format (e.g. dw = x1 x y0 - y1 x x0
etc. as in NxNet tutorials on INRC). For the same, I am using the nengo.Connection
object to access the connection mapping on Loihi (not sure if this is the right way to effect my learning rule) using the following code:
loihi_sim = nengo_loihi.Simulator(net) # net is my sample network.
board = loihi_sim.sims["loihi"].board
synapse = loihi_sim.model.objs[conn] # conn is the nengo.Connection object.
board.find_synapse(synapses)
and it throws following error:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-9-5f020689a243> in <module>
1 synapses = loihi_sim.model.objs[conn]
----> 2 board.find_synapse(synapses)
~/nengo-loihi/nengo_loihi/hardware/nxsdk_objects.py in find_synapse(self, synapse)
85
86 def find_synapse(self, synapse):
---> 87 return self.synapse_index[synapse]
88
89
TypeError: unhashable type: 'dict'
Upon looking at the loihi_sim.model.objs
output, I see that it has
.
.
.
<Connection at 0x7f9c47834b50 from <Node (unlabeled) at 0x7f9c47834910> to <Neurons of <Ensemble (unlabeled) at 0x7f9cd4fb9700>>>: {}})
i.e. an empty dictionary as the value of the conn
object.
Can someone help me how to access the nengo.Connection
object on Loihi and specify a custom learning rule? Thank you for your time!