point_vox_template.yaml

resume: false
test_only: false
num_workers: 10

required_devices: 1
no_test: false
debug: false
log2tb: true
allow_double_bs: false
seed: 0
distributed: false
test_freq: 2
print_freq: 5

dataset:
  DATASET_NAMES: [scannet]
  DATA_PATHS: ['/path/to/datalist.npy']
  BATCHSIZE_PER_REPLICA: 32
  LABEL_TYPE: sample_index
  DATA_TYPE: point_vox
  VOX: True
  POINT_TRANSFORMS:
    - name: randomcuboid
      crop: 0.5
      npoints: 10000
      randcrop: 1.0
      aspect: 0.75
    - name: randomdrop
      crop: 0.2
    - name: multiscale
    - name: RandomFlip
    - name: RandomRotateAll
    - name: RandomScale
    - name: ToTensor
  COLLATE_FUNCTION: "point_vox_moco_collator"
  INPUT_KEY_NAMES: ["points", "points_moco", "vox", "vox_moco"]
  DROP_LAST: True

optimizer:
  name: "sgd"
  weight_decay: 0.0001
  momentum: 0.9
  nesterov: False
  num_epochs: 1000
  lr:
    name: "cosine"
    base_lr: 0.12
    final_lr: 0.00012

model:
  name: "Pointnet1X_Unet256"
  model_dir: "checkpoints/pointnet1x_Unet256/"
  model_input: ["points", "points_moco", "vox", "vox_moco"]
  model_feature: [["fp2"], ["fp2"], ["plane7"], ["plane7"]]
  arch_point: "pointnet"
  args_point:
    scale: 1
    use_mlp: True
    mlp_dim: [512, 512, 128]
  arch_vox: "unet"
  args_vox:
    use_mlp: True
    mlp_dim: [256, 256, 128]

loss:
  name: "NCELossMoco"
  args:
    two_domain: True
    LOSS_TYPE: NPID,CMC
    OTHER_INPUT: True
    within_format_weight0: 0.5
    within_format_weight1: 0.5
    across_format_weight0: 0.5
    across_format_weight1: 0.5
    NCE_LOSS:
      NORM_EMBEDDING: True
      TEMPERATURE: 0.1
      LOSS_TYPE: cross_entropy
      NUM_NEGATIVES: 131072
      EMBEDDING_DIM: 128