defaults:
  - _self_
hydra:
  run:  
    dir: ${logdir}
_target_: agent.eval.eval_diffusion_agent.EvalDiffusionAgent

name: ${env_name}_eval_diffusion_mlp_ta${horizon_steps}_td${denoising_steps}
logdir: ${oc.env:DPPO_LOG_DIR}/d3il-eval/${name}/${now:%Y-%m-%d}_${now:%H-%M-%S}_${seed}
base_policy_path:
normalization_path: ${oc.env:DPPO_DATA_DIR}/d3il/avoid_m1/normalization.npz

seed: 42
device: cuda:0
env_name: avoiding-m5
obs_dim: 4
action_dim: 2
denoising_steps: 20
cond_steps: 1
horizon_steps: 4
act_steps: 4
ft_denoising_steps: 0

n_steps: 25
render_num: 40

plotter:
  _target_: env.plot_traj.TrajPlotter
  env_type: avoid
  normalization_path: ${normalization_path}

env:
  n_envs: 40
  name: ${env_name}
  max_episode_steps: 100
  reset_at_iteration: True
  save_video: False
  best_reward_threshold_for_success: 2
  save_full_observations: True
  wrappers:
    d3il_lowdim:
      normalization_path: ${normalization_path}
    multi_step:
      n_obs_steps: ${cond_steps}
      n_action_steps: ${act_steps}
      max_episode_steps: ${env.max_episode_steps}
      pass_full_observations: ${env.save_full_observations}
      reset_within_step: False

model:
  _target_: model.diffusion.diffusion_eval_ft.DiffusionEval
  ft_denoising_steps: ${ft_denoising_steps}
  predict_epsilon: True
  denoised_clip_value: 1.0
  #
  network_path: ${base_policy_path}
  network:
    _target_: model.diffusion.mlp_diffusion.DiffusionMLP
    time_dim: 16
    mlp_dims: [512, 512, 512]
    activation_type: ReLU
    residual_style: True
    cond_dim: ${eval:'${obs_dim} * ${cond_steps}'}
    horizon_steps: ${horizon_steps}
    action_dim: ${action_dim}
  horizon_steps: ${horizon_steps}
  obs_dim: ${obs_dim}
  action_dim: ${action_dim}
  denoising_steps: ${denoising_steps}
  device: ${device}