s3dis_with_stuff_nano.yaml

# @package _global_

# to execute this experiment run:
# python train.py experiment=panoptic/s3dis_with_stuff_nano

defaults:
  - override /datamodule: panoptic/s3dis_with_stuff_nano.yaml
  - override /model: panoptic/nano-2.yaml
  - override /trainer: gpu.yaml

# all parameters below will be merged with parameters from default configurations set above
# this allows you to overwrite only specified parameters

trainer:
  max_epochs: 2000

model:
  optimizer:
    lr: 0.1
    weight_decay: 1e-2

  partitioner:
    regularization: 10
    x_weight: 5e-2
    cutoff: 300

  partition_every_n_epoch: 20

logger:
  wandb:
    project: "spt_s3dis"
    name: "NANO"

# metric based on which models will be selected
optimized_metric: "val/pq"

# modify checkpointing callbacks to adapt to partition_every_n_epoch
# being potentially different
callbacks:
  model_checkpoint:
    every_n_epochs: ${eval:'max(${trainer.check_val_every_n_epoch}, ${model.partition_every_n_epoch})'}

  early_stopping:
    strict: False