curobo.opt.particle.parallel_es module

class curobo.opt.particle.parallel_es.ParallelESConfig(d_action: 'int', action_lows: 'List[float]', action_highs: 'List[float]', action_horizon: 'int', horizon: 'int', n_iters: 'int', cold_start_n_iters: 'Union[int, None]', rollout_fn: 'RolloutBase', tensor_args: 'TensorDeviceType', use_cuda_graph: 'bool', store_debug: 'bool', debug_info: 'Any', n_problems: 'int', num_particles: 'Union[int, None]', sync_cuda_time: 'bool', use_coo_sparse: 'bool', gamma: float, sample_mode: curobo.opt.particle.particle_opt_base.SampleMode, seed: int, calculate_value: bool, store_rollouts: bool, init_mean: float, init_cov: float, base_action: curobo.opt.particle.parallel_mppi.BaseActionType, step_size_mean: float, step_size_cov: float, null_act_frac: float, squash_fn: curobo.opt.particle.particle_opt_utils.SquashType, cov_type: curobo.opt.particle.parallel_mppi.CovType, sample_params: curobo.util.sample_lib.SampleConfig, update_cov: bool, random_mean: bool, beta: float, alpha: float, kappa: float, sample_per_problem: bool, learning_rate: float = 0.1)

Bases: ParallelMPPIConfig

Parameters:
  • d_action (int) –

  • action_lows (List[float]) –

  • action_highs (List[float]) –

  • action_horizon (int) –

  • horizon (int) –

  • n_iters (int) –

  • cold_start_n_iters (int | None) –

  • rollout_fn (RolloutBase) –

  • tensor_args (TensorDeviceType) –

  • use_cuda_graph (bool) –

  • store_debug (bool) –

  • debug_info (Any) –

  • n_problems (int) –

  • num_particles (int | None) –

  • sync_cuda_time (bool) –

  • use_coo_sparse (bool) –

  • gamma (float) –

  • sample_mode (SampleMode) –

  • seed (int) –

  • calculate_value (bool) –

  • store_rollouts (bool) –

  • init_mean (float) –

  • init_cov (float) –

  • base_action (BaseActionType) –

  • step_size_mean (float) –

  • step_size_cov (float) –

  • null_act_frac (float) –

  • squash_fn (SquashType) –

  • cov_type (CovType) –

  • sample_params (SampleConfig) –

  • update_cov (bool) –

  • random_mean (bool) –

  • beta (float) –

  • alpha (float) –

  • kappa (float) –

  • sample_per_problem (bool) –

  • learning_rate (float) –

learning_rate: float = 0.1
class curobo.opt.particle.parallel_es.ParallelES(config=None)

Bases: ParallelMPPI, ParallelESConfig

Base optimization solver class

Parameters:

config (ParallelESConfig | None) – Initialized with parameters from a dataclass.

_compute_mean(w, actions)
_exp_util(total_costs)