ego_gmm_clsft.yaml

# @package _global_

defaults:
  # - override /trainer: ddp
  - override /model: ego_gmm

model:
  model_config:
    lr: 1e-4
    lr_min_ratio: 0.05
    token_processor:
      map_token_sampling: # open-loop
        num_k: 1 # for k nearest neighbors
        temp: 1.0 # uniform sampling
      agent_token_sampling: # closed-loop
        num_k: 1 # for k nearest neighbors
        temp: 1.0
    validation_rollout_sampling:
      criterium: topk_prob # {topk_prob, topk_prob_sampled_with_dist}
      num_k: 3 # for k most likely
      temp_mode: 1e-3
      temp_cov: 1e-3
    training_rollout_sampling:
      criterium: topk_prob_sampled_with_dist # {topk_prob, topk_prob_sampled_with_dist}
      num_k: 3 # for k nearest neighbors, set to -1 to turn-off closed-loop training
      temp_mode: 1e-3
      temp_cov: 1e-3
    finetune: true
  
ckpt_path: BC_PRETRAINED_MODEL.ckpt

trainer:
  limit_train_batches: 1.0
  limit_val_batches: 0.1
  check_val_every_n_epoch: 1

data:
  train_batch_size: 10
  val_batch_size: 10
  test_batch_size: 10
  num_workers: 10

action: finetune