This are anonymized code snippets from the S-RNN repository. The complete repository is currently hosted in a private GitHub repository. It will be made public.

The set of files included here implements S-RNN on top of the MI-RNN outputs on the Google-13 dataset. Details below.

## Project Setup/Directory Structure

The project is setup as a pip package from local directory. Perform

    pip install -e . 

This is so that imports work properly within the virtual-environment and
project files can be shared across projects.

- `divideandconquer.common.*` has all the implementations used throughout this project. `divideandconquer.common.graphs` will have the computation graphs for S-RNN.
- `divideandconquer.stackedLSTM.*` illustrates how `S-RNN` can be used on top of `MI-RNN` for `google-13` dataset. The google-13 dataset can be downloaded from [here](https://ai.googleblog.com/2017/08/launching-speech-commands-dataset.html). The code for generating the `MI-RNN` outputs can be found [here](https://github.com/microsoft/EdgeML). We have included the featurization code.
