sim2sim

example/python/exported/read.py

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+import onnx
+
+# ONNX 모델 열기
+model = onnx.load("policy.onnx")
+
+# 모델 구조 출력
+print(onnx.helper.printable_graph(model.graph))

example/python/params/agent.yaml

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+seed: 42
+device: cuda:0
+num_steps_per_env: 24
+max_iterations: 300
+empirical_normalization: null
+obs_groups: {}
+clip_actions: null
+save_interval: 50
+experiment_name: unitree_go2_flat
+run_name: ''
+logger: tensorboard
+neptune_project: isaaclab
+wandb_project: isaaclab
+resume: false
+load_run: .*
+load_checkpoint: model_.*.pt
+class_name: OnPolicyRunner
+policy:
+  class_name: ActorCritic
+  init_noise_std: 1.0
+  noise_std_type: scalar
+  actor_obs_normalization: false
+  critic_obs_normalization: false
+  actor_hidden_dims:
+  - 128
+  - 128
+  - 128
+  critic_hidden_dims:
+  - 128
+  - 128
+  - 128
+  activation: elu
+algorithm:
+  class_name: PPO
+  num_learning_epochs: 5
+  num_mini_batches: 4
+  learning_rate: 0.001
+  schedule: adaptive
+  gamma: 0.99
+  lam: 0.95
+  entropy_coef: 0.01
+  desired_kl: 0.01
+  max_grad_norm: 1.0
+  value_loss_coef: 1.0
+  use_clipped_value_loss: true
+  clip_param: 0.2
+  normalize_advantage_per_mini_batch: false
+  rnd_cfg: null
+  symmetry_cfg: null