Deprecated as of March 11, 2022! Use https://github.com/neuroailab/convrnns instead (includes pretrained models).
Run models in time.
git clone https://github.com/neuroailab/tnn.git
pip install -e tnn
(-e installs a developer version such that you can always update your code to the latest)
Note: networkx==1.11 is the latest version of the networkx package that works with this package (higher versions of networkx will not work).
Look at tutorials. tutorials/alexnet_example.py demonstrates the basic unrolling API with AlexNet. tutorials/customcell_example.py shows how to pass a custom cell to a model, and add edges.
tnn/convrnn.py contains examples of standard ConvRNN cells in the literature. tnn/resnetrnn.py contains the Reciprocal Gated Cell implementation (see https://arxiv.org/abs/1807.00053 for details). tnn/efficientgaternn.py contains the Efficient Gated Unit cell implementation used in https://arxiv.org/abs/2006.12373.
json contains a set of example graphs including 5 layer LSTM and Reciprocal Gated models. To use them with the customcell_example.py, set the global variables MODEL_JSON = 5L_imnet128_lstm345 and CUSTOM_CELL = tnn_ConvLSTMCell. You will also need to set the INPUT_LAYER and READOUT_LAYER to match the model JSON.
- Jonas Kubilius (MIT)
- Daniel L.K. Yamins (Stanford)
- Maryann Rui (Berkeley)
- Harry Bleyan (MIT)
- Aran Nayebi (Stanford)
- Daniel Bear (Stanford)
MIT