ResNet 34 Ensemble Predictions on TinyImageNet

Predictions generated by an ensemble of 4 ResNet 34 Deep Neural Networks Trained on TinyImagenet, as used in repository https://anonymous.4open.science/r/ensemble_attention-7616/README.md. Ensembles are trained to encourage/discourage predictive diversity. Each timestamped folder contains individual training runs, with the labels and probabilistic predictions of the ensemble on 1) the training set (train_labels.npy, train_preds.npy) and 2) the test set (ind_labels.npy, ind_preds.npy) for tinyimagenet. The file (tinyimagenet/resnet34/version_0/hparams.yaml) contains specific hyperparameters used on a particular training run. Figures visualizing training results can be generated by:
1.unzipping the four folders in to the directory `ensemble_attention/scripts/outputs/` 
2. running the script `ensemble_attention/scripts/vis_scripts/all_weights_resnet34_tinyimagenet.py`.