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Hoffman Lab Application

Code sample for Hoffman lab application.

Code description:

The code trains a U-net autoencoder in a supervised fashion. Both the input and output are part of the .npy file, provided in this repository.

Dependency:

Pytorch 1.9.0
Numpy 1.21.2
matplotlib 3.4.3

How to run:

Load an anaconda pytorch environment.
Run the code as python DLHoffmanLabSample.py

Outputs:

Lossfile_train.txt
SavedParameters.pth
And a pair of images showing contact maps and distance maps after every two iterations, these files are named as follows
Autoencoder_contact<epoch number>.png and Autoencoder_distance<epoch number>.png

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