- PyTorch 1.5.1+
- Follow instructions here to set it up locally (depends on your environment)
First, you need to setup the CLS module before using it with any of the available frameworks.
- Change into the
cls_module
directory - Execute the
python setup.py develop
command to install the package and its dependencies
This is an implementation of the one-shot generalization benchmark introduced by Lake. The code is available under the
directory frameworks/lake
.
To run an experiment using the Lake framework, you will need a valid configuration file. There is an existing configuration
file located in frameworks/lake/config.json
with the default configuration.
Run the experiment using python oneshot_cls.py --config path/to/config.json
The code is available under frameworks/cfsl
and is derived from https://github.com/AntreasAntoniou/FewShotContinualLearning
To run the experiments with CLS, you can simply modify the configuration file in omniglot_cls.json
and then run the experiment using bash omniglot_cls.sh GPU_ID latest
.
Note: Set GPU_ID
to 0
if you are not using a GPU, and 1
if you are using a GPU.