modelnet40.yaml

# pytorch_lightning==1.7.2
seed_everything: 0
trainer:
  sync_batchnorm: true
  # gradient_clip_val: null
  # gradient_clip_algorithm: null
  max_epochs: 150
  precision: 16
model:
  num_points: 1024
  tokenizer_num_groups: 64
  tokenizer_group_size: 32
  tokenizer_group_radius: null # 0.15 works best
  encoder_dim: 384
  encoder_depth: 12
  encoder_heads: 6
  encoder_dropout: 0.0
  encoder_attention_dropout: 0.0
  encoder_drop_path_rate: 0.2
  encoder_add_pos_at_every_layer: true
  cls_head: mlp
  cls_head_dim: 256
  cls_head_dropout: 0.5
  cls_head_pooling: mean+max
  loss_label_smoothing: 0.2
  learning_rate: 0.001
  optimizer_adamw_weight_decay: 0.05
  lr_scheduler_linear_warmup_epochs: 10
  lr_scheduler_linear_warmup_start_lr: 1.0e-06
  lr_scheduler_cosine_eta_min: 1.0e-06
  pretrained_ckpt_path: null
  train_transformations:
  - "scale"
  - "center"
  - "unit_sphere"
  val_transformations:
  - "center"
  - "unit_sphere"
  transformation_scale_min: 0.6
  transformation_scale_max: 1.4
  transformation_scale_symmetries: [0, 0, 0] # TODO: check if [1,0,1] is better/worse
  transformation_rotate_dims: [1]
  transformation_rotate_degs: 90
  transformation_translate: 0.2
  transformation_height_normalize_dim: 1
  log_tsne: false
  log_confusion_matrix: false

data:
  class_path: point2vec.datasets.ModelNet40Ply2048DataModule
  init_args:
    data_dir: ./data/modelnet40_ply_hdf5_2048
    batch_size: 32