importing and integration

README.md

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-# Closed Form Solution of Neural ODEs
+# Closed-form Continuous-depth Models
 
+This archive is the code supplementary materials of the paper Closed-form Continuous-depth Models
+
+## Requirements
+
+- Python3.6 or newer
+- Tensorflow 2.4 or newer
+- PyTorch 1.8 or newer
+- pytorch-lightning 1.3.0 or newer
+- scikit-learn 0.24.2 or newer
+
+## Module description
+
+- ```tf_cfc.py``` Implementation of the CfC (various versions) in Tensorflow 2.x
+- ```torch_cfc.py``` Implementation of the CfC (various versions) in PyTorch
+- ```train_physio.py``` Trains the CfC models on the Physionet 2012 dataset in PyTorch (code adapted from Rubanova et al. 2019)
+- ```train_xor.py``` Trains the CfC models on the XOR dataset in Tensorflow (code adapted from Lechner & Hasani, 2020)
+- ```train_imdb.py``` Trains the CfC models on the IMDB dataset in Tensorflow (code adapted from Keras examples website)
+- ```train_walker.py``` Trains the CfC models on the Walker2d dataset in Tensorflow (code adapted from Lechner & Hasani, 2020)
+- ```irregular_sampled_datasets.py``` Datasets (same splits) from Lechner & Hasani (2020)
+- ```duv_physionet.py``` and ```duv_utils.py``` Physionet dataset (same split) from Rubanova et al. (2019)
+
+## Usage
+
+All training scripts except the following three flags
+
+- ```no_gate``` Runs the CfC without the (1-sigmoid) part
+- ```minimal``` Runs the CfC direct solution
+- ```use_ltc``` Runs an LTC with a semi-implicit ODE solver instead of a CfC
+- ```use_mixed``` Mixes the CfC's RNN-state with a LSTM to avoid vanishing gradients
+
+If none of these flags are provided, the full CfC model is used
+
+For instance 
+
+```bash
+python3 train_physio.py
+```
+
+train the full CfC model on the Physionet dataset.
+
+Similarly
+
+```bash
+train_walker.py --minimal
+```
+
+runs the direct CfC solution on the walker2d dataset.
+
+For downloading the Walker2d dataset of Lechner & Hasani 2020, run 
+
+```bash
+source download_dataset.sh
+```
 

download_dataset.sh

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+#!/bin/bash
+
+mkdir data
+mkdir data/person
+
+wget https://pub.ist.ac.at/~mlechner/datasets/walker.zip
+unzip walker.zip -d data/
+rm walker.zip