Point-BERT.yaml

optimizer : {
  type: AdamW,
  kwargs: {
  lr : 0.0005, 
  weight_decay : 0.05
}}

scheduler: {
  type: CosLR,
  kwargs: {
    epochs: 300,
    initial_epochs : 3
}}

dataset : {
  train : { _base_: cfgs/dataset_configs/ShapeNet-55.yaml, 
            others: {subset: 'train', npoints: 1024, whole: True}},
  val : { _base_: cfgs/dataset_configs/ModelNet40.yaml, 
            others: {subset: 'test'}},
  extra_train : { _base_: cfgs/dataset_configs/ModelNet40.yaml, 
            others: {subset: 'train'}}}
model : {
  NAME: Point_BERT, 
  m: 0.999,
  T: 0.07,
  K: 16384,
  
  transformer_config: {
    mask_ratio: [0.25, 0.45], 
    trans_dim: 384, 
    depth: 12, 
    drop_path_rate: 0.1, 
    cls_dim: 512, 
    replace_pob: 0., 
    num_heads: 6, 
    moco_loss: False, 
    dvae_loss: True, 
    cutmix_loss: True, 
    return_all_tokens: False, 
  },
  dvae_config : {
    group_size: 32, 
    num_group: 64, 
    encoder_dims: 256,
    num_tokens: 8192,
    tokens_dims: 256, 
    decoder_dims: 256, 
    ckpt: 'Need to be set' # set the dVAE weight here
  }}

total_bs : 128
step_per_update : 1
max_epoch : 300

consider_metric: CDL1