Experiments for the masters thesis of Martin Thoma
Every experiment is a YAML file. See the experiments folder for some examples.
- matplotlib
- Tensorflow 1.0
- Keras 2.0 (adjusted preprocessing/image.py, see misc directory)
- seaborn
If you get TypeError: __init__() got an unexpected keyword argument 'hsv_augmentation'
you didn't adjust the image.py
. Just copy the one in
the misc folder to python -c "import keras.preprocessing.image as k;print(k.__file__)"
./run_training.py -f experiments/cifar100_baseline.yaml
: Train a model. Downloads everything by its own./analyze_training.py -d artifacts/cifar100_baseline
: Show some training statistics./inference_timing.py -f experiments/cifar100_baseline.yaml
: Run inference on a given trained model and measure the time./eval_ensemble.py -f ensemble/cifar100_baseline.yaml
: Evaluate an ensemble./visualize.py --cm artifacts/cifar100_root/cm-test.json
: Confusion matrix optimization./create_cm.py --indices cm.indices.pickle -f experiments/cifar100_root-g5.yaml
Measuring inference time needs about 2 minutes:
$ ./inference_timing.py -f experiments/cifar10_baseline.yaml
Measuring training time takes about 70 minutes:
$ ./run_training.py -f experiments/cifar10_baseline.yaml