NB: I NEED TO UPDATE THIS README
installation:
conda env create -n activmask --file environment.yml
source install.sh
.
training:
A config file needs to be defined to run the experiments, e.g.:
gradmask train --config gradmask/config/mnist.yml
monitoring:
The code right now will log all experiments in the logs/experiments.csv
file.
The time of saving, git hash, config, and best accuracy on the valid set is
saved.
skopt
Steps to launch bayesian hyperparameters search:
- In your
.yml
config file, choose the parameters you want to optimize (i.e. learning rate). - Replace the value with the search parameters. For example:
search the learning rate in the range (0.01, 0.0001), on a log scale. Examples..
# Optimizer optimizer: Adam: lr: "Real(10**-4, 10**-2, 'log-uniform')"
- Launch your config file with
activmask train-skopt --config config/path.yml
An config example can be found in config/mnist_skopt.yml