Graded spike payload in pre-synaptic trace updates - floating-pt and bit-approximate-loihi#607
Graded spike payload in pre-synaptic trace updates - floating-pt and bit-approximate-loihi#607
floating-pt and bit-approximate-loihi#607Conversation
gkarray
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PhilippPlank,
awintel,
elvinhajizada,
mathisrichter and
weidel-p
mathisrichter
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mathisrichter
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I have not reviewed this to a point, where I could approve or block it, so I am just leaving comments.
It all looks good though, at least from a high level coding-style point of view. I only added a few minor remarks.
The one thing we could maybe improve are the known-value tests. It is not clear where the known values come from or how we know they are correct. There are also so many that the significance of individual numbers is unclear. Please keep in mind that someone will at some point look at this code and need to understand why all these values as deemed correct. Make sure that it is very easy to understand that from the code. That person could be yourself one year from now. :)
PhilippPlank
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This concept of how the payload modifies the traces seems quite complicated. We should have a good example in the learning tutorial to show what will happen.
If there is no issue for that yet, please create one.
…pikes # Conflicts: # src/lava/magma/core/model/py/connection.py
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Issue Number: #606
Objective of pull request: As a user of the learning API, I would like to use graded spike payloads to update pre-synaptic traces in order to implement more complex learning algorithms. Especially, this is critical for prototype-based learning approaches.
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