run_name: cdit_debug

# training setup
results_dir: logs
train: True
batch_size: 1
num_workers: 12
model: CDiT-XL/2
lr: 8e-5

# normalization for the action space
normalize: True
grad_clip_val: 10.0
context_size: 4

# distance bounds for distance and action and distance predictions 
distance:
  min_dist_cat: -64
  max_dist_cat: 64

# action output params
len_traj_pred: 64

# dataset specific parameters
image_size: 224
datasets:
  # airvln_16:
  #   data_folder: data/airvln_16
  #   train: data_splits/airvln_16/train/ # path to train folder with traj_names.txt
  #   test: data_splits/airvln_16/test/ # path to test folder with traj_names.txt
  #   goals_per_obs: 4
  airvln_1episode:
    data_folder: data/airvln_1episode
    train: data_splits/airvln_1episode/train/ # path to train folder with traj_names.txt
    test: data_splits/airvln_1episode/test/ # path to test folder with traj_names.txt
    goals_per_obs: 4
  # recon:
  #   data_folder: data/recon
  #   train: data_splits/recon/train/ # path to train folder with traj_names.txt
  #   test: data_splits/recon/test/ # path to test folder with traj_names.txt
  #   goals_per_obs: 4
  # wuhan:
  #   data_folder: data/wuhan
  #   train: data_splits/wuhan/train/ # path to train folder with traj_names.txt
  #   test: data_splits/wuhan/test/ # path to test folder with traj_names.txt
  #   goals_per_obs: 4
  # wuhan_auto:
  #   data_folder: data/wuhan_auto
  #   train: data_splits/wuhan_auto/train/ # path to train folder with traj_names.txt
  #   test: data_splits/wuhan_auto/test/ # path to test folder with traj_names.txt
  #   goals_per_obs: 4
  # tartan_drive:
  #   data_folder: data/tartan
  #   train: data_splits/tartan_drive/train/
  #   test: data_splits/tartan_drive/test/
  #   goals_per_obs: 4
  # sacson:
  #   data_folder: data/sacson
  #   train: data_splits/sacson/train
  #   test: data_splits/sacson/test
  #   goals_per_obs: 4
  # scand:
  #   data_folder: data/scand
  #   train: data_splits/scand/train
  #   test: data_splits/scand/test
  #   goals_per_obs: 4