dataset:
  root: "/path/to/GridNet-HD"
  split_file: "/path/to/GridNet-HD/split.json"
  n_classes: 11
  voxel_size: 0.05  # for KDTree
  pre-processing_num_workers: 8
  max_point_per_class: 1000000 
  class_map:
    - keys: [0, 1, 2, 3, 4] # original values
      value: 0              # new value (remap value)
    - keys: [5]
      value: 1
    - keys: [6, 7]
      value: 2
    - keys: [8, 9, 10, 11]
      value: 3
    - keys: [14]
      value: 4
    - keys: [15]
      value: 5
    - keys: [16]
      value: 6
    - keys: [17, 18]
      value: 7
    - keys: [19]
      value: 8
    - keys: [20]
      value: 9
    - keys: [21]
      value: 10
    - keys: [12, 13, 255]
      value: 255

training:
  batch_size:     8192
  epochs:         10
  learning_rate:  0.001
  weight_decay:   0.0001
  device:         "cuda"
  lr_step_size:   4     # scheduler every 4 epochs
  lr_gamma:       0.1    # decay factor

model:
  hidden_dims: [128, 256, 128, 64]
  ignore_index: 255

logging:
  save_dir: "outputs/run"
  save_freq: 5
  
wandb:
  project: "GridNet-HD_MLP_late_fusion"
  entity: "your-team"