dales.yaml

# @package _global_

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

defaults:
  - override /datamodule: panoptic/dales.yaml
  - override /model: panoptic/spt-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: 400

model:
  optimizer:
    lr: 0.01
    weight_decay: 1e-4

  partitioner:
    regularization: 20
    x_weight: 5e-2
    cutoff: 100

  edge_affinity_loss_lambda: 10

  partition_every_n_epoch: 10

logger:
  wandb:
    project: "spt_dales"
    name: "SPT-64"

# 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