post_pretrain.yaml

optimizer: { type: AdamW, kwargs: { lr: 0.0001, weight_decay: 0.05 } }

scheduler: { type: CosLR, kwargs: { epochs: 100, initial_epochs: 10 } }

dataset:
  {
    train:
      {
        _base_: cfgs/dataset_configs/LabeledHybrid.yaml,
        others: { subset: "train" },
      },
    val:
      {
        _base_: cfgs/dataset_configs/LabeledHybrid.yaml,
        others: { subset: "test" },
      },
    test:
      {
        _base_: cfgs/dataset_configs/LabeledHybrid.yaml,
        others: { subset: "test" },
      },
  }
model:
  {
    NAME: PointTransformer,
    trans_dim: 768,
    depth: 12,
    drop_path_rate: 0.2,
    cls_dim: 87,
    num_heads: 12,
    group_size: 32,
    num_group: 64,
    encoder_dims: 768,
    decoder_depth: 4,
    loss: cdl2,
    weight_center: 1,
  }

npoints: 1024
total_bs: 256
step_per_update: 1
max_epoch: 100
grad_norm_clip: 10