msf235 / test_capacity Goto Github PK

Anonymized code for running simulations for the paper

"Capacity of Group-invariant Linear Readouts from Equivariant Representations:
How many objects can be linearly classified under all possible views?",

submitted to ICLR 2022.


To generate Figure 1, run

python manifold_plots.py

This script is fairly simple and self-explanatory.


To generate Figures 2 and 3, run

python plot_cnn_capacity.py

At the bottom of the plot_cnn_capacity.py script, the plotting function
is called for different panels. Comment out lines to generate specific
figures. This script searches for a match with sets of parameters defined
in cnn_capacity_params.py. To modify parameters used for simulations,
modify the dictionaries in cnn_capacity_params.py or define your own
parameter sets. For a description of different parameter options,
see the docstring for the function cnn_capacity.get_capacity.


cnn_capacity_utils.py contains utility functions. The VGG model can be found
in models/vgg.py. The code for generating datasets can be found in datasets.py.


The code was modified and superficially refactored in preparation for
submission. The simulations haven't been thoroughly tested after this
refactoring so it's not 100% guaranteed that the code is correct.
Fingers crossed that everything works the way it should.