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View Code? Open in Web Editor NEWA Python package for simulating recurrent, biologically-realistic neural networks
License: MIT License
A Python package for simulating recurrent, biologically-realistic neural networks
License: MIT License
The current logging system is pretty slow, since we do some fancy SQL-style joining. It also has some bugs (for example, it reports 1x1 Tensors instead of floats for Layer unit-level attributes.)
To fix this, we need to consider two kinds of attributes: "whole" attributes, like layer.avg_act
, and "part" attributes, like the net
value of a layer's 3rd unit. This will allow us to get rid of the nasty joins.
ObservableMixin
Abstract attributes
A set of "whole" attributes
A set of "part" attributes
Abstract methods
observe_parts_attr(self, attr: str) -> Dict[str, List[Any]]
. Should return a dict that looks like {"unit": [0, 1], "act": [0.3, 0.5]}
.Already implemented methods
observe_whole_attr(self, attr: str) -> Tuple[str, Any]
(this is just a simple getattr)validate_attr()
Logger
Tuple[str, Any]
into a dict).whole
and parts
. Each contains a data frame with the respective logs. We will return this from net.logs()
instead of a single data frame.Other stuff:
logs.py
to make senseNeeded for the Schapiro model.
We should direct people to the project pages instead.
It doesn't document the exception raised.
Hey Noam,
I just realized that the README points users to the Hitchiker's Guide to Python for the Python installation instructions. Since we moved our packaging to Anaconda, we actually want them to install the Anaconda python distribution (https://conda.io/docs/user-guide/install/download.html)
Could you update the README (again, sorry!) to point them there?
Necessary for the Schapiro model
Actually, we want to check it on spec validation.
Please mention and add a prominent link to your Arxiv paper in the readme of this repo. I believe it is https://arxiv.org/abs/1809.04166
Right now, we encode the "unit" number in the dataframe column title. This is annoying and should be fixed.
The link to the Hitchiker's Guide to Python in the README is broken.
Since you've implemented the average KWTA already, that code is no longer needed :)
Necessary for Schapiro Model
Currently, we just check of the object exists. We should (probably) also validate the object's type.
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