deadtrees/configs/config.yaml

# @package _global_

# specify here default training configuration
defaults:
    - _self_
    - trainer: default.yaml
    - model: default.yaml
    - datamodule: deadtrees_combo_dataset_multiclass_rgbn.yaml
    - callbacks: default.yaml
    - logger: wandb.yaml

    - mode: default.yaml

    - experiment: null
    - hparams_search: null

    # optional local config
    - optional local: default.yaml

    # enable color logging
    - override hydra/hydra_logging: colorlog
    - override hydra/job_logging: colorlog

# path to original working directory
# hydra hijacks working directory by changing it to the current log directory,
# so it's useful to have this path as a special variable
# learn more here: https://hydra.cc/docs/next/tutorials/basic/running_your_app/working_directory
work_dir: ${hydra:runtime.cwd}

# path to folder with data
data_dir: ${work_dir}/data/

# pretty print config at the start of the run using Rich library
print_config: True

# disable python warnings if they annoy you
ignore_warnings: True

# evaluate on test set, using best model weights achieved during training
# lightning chooses best weights based on metric specified in checkpoint callback
test_after_training: True

# seed for random number generators in pytorch, numpy and python.random
seed: null

# name of the run is accessed by loggers
# should be used along with experiment mode
name: null