deployment_options.yaml

# Dataset
## Selection
datasets: ["kitti"] # Can contain multiple datasets, e.g. ["darpa", "kitti"]
mode: "testing" # Valid options: "training" and "testing", will also be set by training/testing scripts
experiment: "testing_KITTI_odometry"

# System information
device: "cuda" # "cuda", "cpu", if multiple GPUs: select cuda device via CUDA_VISIBLE_DEVICES=...
store_dataset_in_RAM: False # If false, each scan and normal file will be read from disk
                            # For KITTI requires approximately 50GB RAM/SWAP
num_dataloader_workers: 0 # default: 0

## Comfort options
unsupervised_at_start: True # if False, it starts to train supervised in the first epoch (Identity matching)
inference_only: True # During testing, it does not compute any losses, during training: no impact
log_normals: True
visualize_images: True
visualize_single_img_preprocessing: False

## Performance options
use_jit: False # Only thoroughly tested for inference