train_ddad ========== .. code:: yaml model: name: 'SelfSupModel' optimizer: name: 'Adam' depth: lr: 0.00009 pose: lr: 0.00009 scheduler: name: 'StepLR' step_size: 30 gamma: 0.5 depth_net: name: 'PackNet01' version: '1A' pose_net: name: 'PoseNet' version: '' params: crop: '' min_depth: 0.0 max_depth: 200.0 datasets: augmentation: image_shape: (384, 640) train: batch_size: 2 num_workers: 8 dataset: ['DGP'] path: ['/data/datasets/DDAD/ddad.json'] split: ['train'] depth_type: ['lidar'] cameras: ['camera_01'] repeat: [5] validation: num_workers: 8 dataset: ['DGP'] path: ['/data/datasets/DDAD/ddad.json'] split: ['val'] depth_type: ['lidar'] cameras: ['camera_01'] test: num_workers: 8 dataset: ['DGP'] path: ['/data/datasets/DDAD/ddad.json'] split: ['val'] depth_type: ['lidar'] cameras: ['camera_01']