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The orignal VAE was driven from: https://github.com/lyeoni/pytorch-mnist-VAE/blob/master/pytorch-mnist-VAE.ipynb. For more infromation about the MLR model visit: https://www.biorxiv.org/content/10.1101/2021.02.07.430171v3.full (code: https://github.com/Shekoo93/MLR) 1. Run the Training.py file 2. save the model in output 1 1. Run the modelRun.py 2. in the mVAE file, the function test_outputs() reproduce the images 3. labels_shape and labels_color variables are the numbers associated with the shape and the color of interest Requirements: The model was programmed in Python 3.7.6 . in a torch environment version 1.3.1. The imported packages are listed here: torch, numpy , torch.nn , torch.nn.functional, torch.optim , imageio, os, copy, matplotlib.pyplot , matplotlib.image , torchvision, datasets, transforms, utils, torch.autograd, Variable, torchvision.utils, save_image, sklearn, svm, sklearn.metrics, classification_report, confusion_matrix, tqdm, PIL, Image, ImageOps, ImageEnhance, version as PILLOW_VERSION, joblib, dump, load.
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