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Publish Parkour qwenpi_v3 latency-aware PPO

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latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/README.md ADDED
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+ # Extreme Parkour Go2 — QwenPI v3 latency-aware PPO
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+
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+ Native command policy trained from scratch with the QwenPI v3 RTX 3090 temporal
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+ latency profile. The checkpoint completed 3,000 PPO iterations on one H200.
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+
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+ Training used 6,144 environments, seed 1, 50 Hz control, 10 Hz decisions,
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+ 24 decisions/environment/iteration, control repeat 5, five PPO epochs, four
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+ minibatches, and fixed learning rate `2e-4`.
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+
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+ | Evaluation | Episodes | Return mean ± SD | Raw length mean ± SD | Waypoint progress mean ± SD |
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+ |---|---:|---:|---:|---:|
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+ | QwenPI v3 temporal profile | 100 | 17.1554 ± 4.3398 | 579.28 ± 103.19 | 0.9214 ± 0.1910 |
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+ | 0 ms latency | 100 | 11.8676 ± 4.5410 | 443.73 ± 139.98 | 0.6757 ± 0.3349 |
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+
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+ Both evaluations use 256 parallel environments, seed 1, deterministic policy
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+ means, and a 1,500 raw-control-frame episode cap. See `eval_profile.json` and
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+ `eval_l0.json` for complete metrics and latency counts.
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+
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+ Training run: https://wandb.ai/saberrr-zju/isaaclab-parkour/runs/h7ebvge6
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+
latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/checkpoint.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ size 171687483
latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/eval_l0.json ADDED
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+ {
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+ "identity": {
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+ "checkpoint": "/home/ubuntu/latency-sensitive-bench/third_party/Isaaclab_Parkour/logs/rsl_rl/unitree_go2_parkour/2026-09-16_09-14-41_extreme_parkour_go2_qwenpi_v3_scratch_seed1_3k_h200/model_2999.pt",
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+ "latency_config": "/home/ubuntu/latency-sensitive-bench/configs/training/latency/parkour_zero.yaml",
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+ "latency": {
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+ "method": "fixed",
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+ "env_fps": 50,
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+ "obs_fps": 10,
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+ "profile_path": null
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+ },
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+ "teacher_checkpoint": "/home/ubuntu/model_14999.pt",
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+ "teacher_baseline": false,
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+ "seed": 1
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+ },
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+ "evaluation": {
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+ "num_envs": 256,
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+ "completed_episodes": 100,
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+ "requested_episodes": 100,
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+ "max_episode_steps": 1500,
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+ "control_repeat": 5
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+ },
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+ "metrics": {
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+ "reward_mean": 11.867607007026672,
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+ "reward_std": 4.540987568918352,
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+ "episode_length_raw_mean": 443.73,
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+ "episode_length_raw_std": 139.97552852501963,
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+ "waypoints_mean": 0.6757142857142857,
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+ "waypoints_std": 0.33494135947313863,
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+ "edge_violation_mean": 0.118,
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+ "edge_violation_std": 0.3317770335632049
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+ },
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+ "latency": {
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+ "scope": "all_vector_slots_until_requested_episode_count",
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+ "admissions": 33536,
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+ "drops": 0,
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+ "raw_control_frames": 167463,
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+ "sampled_ms_mean": 0.0
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+ },
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+ "throughput": {
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+ "raw_control_frames": 167463,
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+ "elapsed_seconds": 51.53632309200475,
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+ "raw_control_frames_per_second": 3249.4169151539627
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+ }
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+ }
latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/eval_l0.yaml ADDED
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+ __base__: train.yaml
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+ latency:
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+ method: fixed
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+ fixed_latency_ms: 0
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+ seed: 0
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+ evaluation:
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+ num_envs: 256
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+ episodes: 100
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+ max_episode_steps: 1500
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+ seed: 1
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+ deterministic: true
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+
latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/eval_profile.json ADDED
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+ {
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+ "identity": {
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+ "checkpoint": "/home/ubuntu/latency-sensitive-bench/third_party/Isaaclab_Parkour/logs/rsl_rl/unitree_go2_parkour/2026-09-16_09-14-41_extreme_parkour_go2_qwenpi_v3_scratch_seed1_3k_h200/model_2999.pt",
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+ "latency_config": "/home/ubuntu/latency-sensitive-bench/outputs/latency_rl/parkour/h200_20260916_qwenpi_v3/latency.yaml",
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+ "latency": {
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+ "method": "temporal",
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+ "env_fps": 50,
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+ "obs_fps": 10,
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+ "profile_path": "/home/ubuntu/latency-sensitive-bench/results/profiling/profiles/qwenpi_v3/1x-rtx3090/extreme_parkour_go2/instance_b19d7af6f1bdd95d/profile.json"
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+ },
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+ "teacher_checkpoint": "/home/ubuntu/model_14999.pt",
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+ "teacher_baseline": false,
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+ "seed": 1
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+ },
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+ "evaluation": {
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+ "num_envs": 256,
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+ "completed_episodes": 100,
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+ "requested_episodes": 100,
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+ "max_episode_steps": 1500,
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+ "control_repeat": 5
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+ },
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+ "metrics": {
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+ "reward_mean": 17.155352230072022,
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+ "reward_std": 4.339797412772,
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+ "episode_length_raw_mean": 579.28,
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+ "episode_length_raw_std": 103.19414672931755,
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+ "waypoints_mean": 0.9214285714285714,
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+ "waypoints_std": 0.19099631367315625,
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+ "edge_violation_mean": 0.099,
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+ "edge_violation_std": 0.3364505907261867
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+ },
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+ "latency": {
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+ "scope": "all_vector_slots_until_requested_episode_count",
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+ "admissions": 12433,
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+ "drops": 23919,
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+ "raw_control_frames": 181588,
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+ "sampled_ms_mean": 238.70590165410624
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+ },
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+ "throughput": {
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+ "elapsed_seconds": 53.32690185899264,
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+ "raw_control_frames_per_second": 3405.185631825307
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+ }
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+ }
latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/eval_profile.yaml ADDED
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+ __base__: train.yaml
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+ evaluation:
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+ num_envs: 256
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+ episodes: 100
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+ max_episode_steps: 1500
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+ seed: 1
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+ deterministic: true
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+
latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/provenance.json ADDED
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+ {
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+ "task": "extreme-parkour-go2",
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+ "model": "ppo-command-policy",
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+ "latency_profile_model": "qwenpi_v3",
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+ "status": "evaluated",
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+ "wandb_url": "https://wandb.ai/saberrr-zju/isaaclab-parkour/runs/h7ebvge6",
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+ "checkpoint": "checkpoint.pt",
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+ "checkpoint_bytes": 171687483,
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+ "checkpoint_sha256": "896954eb9e51f2f3ee96b4f82286c330bc57c2b21e16bbfdee023a9bbe373dc1",
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+ "repo_id": "latency-sensitive-bench/profiles",
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+ "profile_sha256": "2abdc10b7e63aeec20bd3688992dec07c813f76c87a1072c20d91b57430e3b52"
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+ "profile": "eval_profile.json",
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+ "zero_latency": "eval_l0.json"
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+ }
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+ }
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+
latency-aware/extreme-parkour-go2/small-policy/ppo-qwenpi_v3-rtx3090-v1/train.yaml ADDED
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+ experiment:
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+ name: extreme_parkour_go2_qwenpi_v3_scratch
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+ seed: 1
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+ env:
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+ name: extreme_parkour_go2
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+ env_fps: 50
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+ obs_fps: 10
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+ simulator_device: cuda:0
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+ latency:
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+ method: temporal
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+ seed: 0
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+ profile_path: profiles/qwenpi_v3/1x-rtx3090/extreme_parkour_go2/instance_b19d7af6f1bdd95d/profile.json
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+ executor:
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+ simulated_worker_capacity: 1
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+ scheduler:
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+ hold_policy: hold
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+ ordering_policy: latest_ready
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+ command:
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+ dimension: 34
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+ horizon: 1
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+ control_repeat: 5
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+ training:
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+ num_envs: 6144
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+ kit_threads: 8
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+ physx_threads: 8
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+ physics_dt: 0.005
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+ decimation: 4
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+ decisions_per_env_per_iteration: 24
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+ max_iterations: 3000
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+ learning_epochs: 5
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+ minibatches: 4
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+ learning_rate: 0.0002
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+ learning_rate_schedule: fixed
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+