seed: 42


# Models are instantiated using skrl's model instantiator utility
# https://skrl.readthedocs.io/en/latest/api/utils/model_instantiators.html
models:
  separate: True
  policy:  # see gaussian_model parameters
    class: GaussianMixin
    clip_actions: False
    clip_log_std: True
    min_log_std: -20.0
    max_log_std: 2.0
    initial_log_std: -2.9
    fixed_log_std: True
    network:
      - name: net
        input: OBSERVATIONS
        layers: [1024, 512]
        activations: relu
    output: ACTIONS
  value:  # see deterministic_model parameters
    class: DeterministicMixin
    clip_actions: False
    network:
      - name: net
        input: OBSERVATIONS
        layers: [1024, 512]
        activations: relu
    output: ONE
  discriminator:  # see deterministic_model parameters
    class: DeterministicMixin
    clip_actions: False
    network:
      - name: net
        input: OBSERVATIONS
        layers: [1024, 512]
        activations: relu
    output: ONE


# Rollout memory
# https://skrl.readthedocs.io/en/latest/api/memories/random.html
memory:
  class: RandomMemory
  memory_size: -1  # automatically determined (same as agent:rollouts)

# AMP memory (reference motion dataset)
# https://skrl.readthedocs.io/en/latest/api/memories/random.html
motion_dataset:
  class: RandomMemory
  memory_size: 200000

# AMP memory (preventing discriminator overfitting)
# https://skrl.readthedocs.io/en/latest/api/memories/random.html
reply_buffer:
  class: RandomMemory
  memory_size: 1000000


# AMP agent configuration (field names are from AMP_DEFAULT_CONFIG)
# https://skrl.readthedocs.io/en/latest/api/agents/amp.html
agent:
  class: AMP
  rollouts: 16
  learning_epochs: 6
  mini_batches: 2
  discount_factor: 0.99
  lambda: 0.95
  learning_rate: 5.0e-05
  learning_rate_scheduler: null
  learning_rate_scheduler_kwargs: null
  state_preprocessor: RunningStandardScaler
  state_preprocessor_kwargs: null
  value_preprocessor: RunningStandardScaler
  value_preprocessor_kwargs: null
  amp_state_preprocessor: RunningStandardScaler
  amp_state_preprocessor_kwargs: null
  random_timesteps: 0
  learning_starts: 0
  grad_norm_clip: 0.0
  ratio_clip: 0.2
  value_clip: 0.2
  clip_predicted_values: True
  entropy_loss_scale: 0.0
  value_loss_scale: 2.5
  discriminator_loss_scale: 5.0
  amp_batch_size: 512
  task_reward_weight: 0.0
  style_reward_weight: 1.0
  discriminator_batch_size: 4096
  discriminator_reward_scale: 2.0
  discriminator_logit_regularization_scale: 0.05
  discriminator_gradient_penalty_scale: 5.0
  discriminator_weight_decay_scale: 1.0e-04
  # rewards_shaper_scale: 1.0
  time_limit_bootstrap: False
  # logging and checkpoint
  experiment:
    directory: "humanoid_amp_run"
    experiment_name: ""
    write_interval: auto
    checkpoint_interval: auto


# Sequential trainer
# https://skrl.readthedocs.io/en/latest/api/trainers/sequential.html
trainer:
  class: SequentialTrainer
  timesteps: 80000
  environment_info: log