train_base.yaml

defaults:
  - task: metaworld_ml45
  - algo: quest
  - _self_

# set the path to your data and experiments directories
output_prefix: ./experiments
data_prefix: ./data

exp_name: debug # 
variant_name: null
seed: 10000
device: cuda:0
stage: null # 0 - pretrain autoencoder, 1 - train multitask, 2 - finetune multitask
make_unique_experiment_dir: true # if true, it will create unique experiment directories with name run_00X within that experiment directory, use when debugging
logging_folder: training

checkpoint_path: null


train_dataloader:
  _target_: torch.utils.data.DataLoader
  batch_size: 128
  shuffle: true
  num_workers: 6
  persistent_workers: false
  pin_memory: true
  multiprocessing_context: fork
  # prefetch_factor: 2

training:
  n_epochs: 100
  grad_clip: 100.
  save_interval: 10
  log_interval: 100
  use_amp: false
  use_tqdm: true
  do_profile: false
  save_all_checkpoints: false
  auto_continue: false # if true, it will automatically continue from the end of stage n training for stage n+1 training
  load_obs: true
  cut: 0

  # resume a training run
  resume: false
  resume_path: ""

rollout:
  enabled: true
  interval: 10
  rollouts_per_env: 1
  max_episode_length: ${task.horizon}
  n_video: 0
  num_parallel_envs: 1


logging:
  group: null
  mode: online # set logging.mode=disabled to disable wandb
  project: quest # TODO: change this to your wandb project name
  resume: true
  save_code: true