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DeepConvLSTM_py3

DeepConvLSTM implemented in python 3 and pytorch

Included is an implementation of DeepConvLSTM in python 3 and torch, along with a jupyter notebook giving an example of training and testing the model on the Opportunity challenge dataset.

Opportunity example notebook

To interact with the notebook, you can use pipenv (https://pypi.org/project/pipenv/) to create a virtual environment with all of the requirements in the included pipfile installed.

After installing pipenv, just run

pipenv install

in the directory containing the pipfile, then

pipenv run jupyter notebook

and choose opportunity_example.ipynb.

Main script

After installing all dependencies with pipenv as above you will be able to run the main DeepConvLSTM_py3.py script. Use

pipenv run python3 DeepConvLSTM_py3.py -h

for a list of command line options.

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DeepConvLSTM implemented in python 3 and pytorch

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  • Jupyter Notebook 83.0%
  • Python 17.0%