Can't slice learning rule input?

[jgosmann]

#1310 added the possibility of arbitrarily sized inputs to learning rules, however it doesn't seem possible to slice into the input. I'm getting the following error:

  File "/home/jgosmann/Documents/projects/imem/imem/tcm.py", line 245, in __init__
    self.target.output[start:end], conn.learning_rule[1:])
TypeError: 'LearningRule' object is not subscriptable

That means I'm still stuck at not being able to implement multiple error signals (see #1307).

Or I'm doing something wrong and I'm completely blind to it ... (which is very well possible to).

[jgosmann]

As a workaround it is possible to combine the error signals in a node and then connect that node to the learning rule.

[jgosmann]

Though, I am not sure that the workaround actually works. I'm getting weird results, but cannot debug it right now.

[jgosmann]

Just realized that I need this functionality more badly than I thought, so I guess I'm going to debug it after all.

[jgosmann]

Found the problem why the workaround wasn't working: The error signal needs to be sliced in the learning rule's step function. If it is sliced in the make_step function creating the step function, it will not work.