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Follow-up doc nits from PR #465 (#476)
## Summary Addresses two nits from the PR #465 review that were approved but not resolved before merge: - Use the `python` alias instead of `/isaac-sim/python.sh` in all RL workflow doc pages - Remove `--headless` as a default flag in the training command examples Signed-off-by: Clemens Volk <cvolk@nvidia.com>
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docs/pages/example_workflows/reinforcement_learning/step_1_environment_setup.rst

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@@ -159,7 +159,7 @@ To validate the environment loads correctly, run one training iteration and chec
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.. code-block:: bash
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/isaac-sim/python.sh submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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python submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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--external_callback isaaclab_arena.environments.isaaclab_interop.environment_registration_callback \
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--task lift_object \
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--num_envs 64 \

docs/pages/example_workflows/reinforcement_learning/step_2_policy_training.rst

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.. code-block:: bash
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/isaac-sim/python.sh submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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python submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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--external_callback isaaclab_arena.environments.isaaclab_interop.environment_registration_callback \
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--task lift_object \
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--num_envs 512 \
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--max_iterations 12000 \
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--headless
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--max_iterations 12000
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.. tip::
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Add ``--headless`` to suppress the GUI when running on a headless server.
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Checkpoints are written to ``logs/rsl_rl/generic_experiment/<timestamp>/``.
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The agent configuration is saved alongside as ``params/agent.yaml``,
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.. code-block:: bash
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/isaac-sim/python.sh submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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python submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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--external_callback isaaclab_arena.environments.isaaclab_interop.environment_registration_callback \
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--task lift_object \
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--num_envs 512 \
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--max_iterations 12000 \
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--headless \
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agent.policy.activation=relu \
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agent.algorithm.learning_rate=0.001
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.. code-block:: bash
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/isaac-sim/python.sh -m tensorboard.main --logdir logs/rsl_rl
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python -m tensorboard.main --logdir logs/rsl_rl
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During training, each iteration prints a summary to the console:
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.. code-block:: bash
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/isaac-sim/python.sh submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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python submodules/IsaacLab/scripts/reinforcement_learning/rsl_rl/train.py \
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--external_callback isaaclab_arena.environments.isaaclab_interop.environment_registration_callback \
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--task lift_object \
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--num_envs 512 \

docs/pages/example_workflows/reinforcement_learning/step_3_evaluation.rst

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.. code-block:: bash
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/isaac-sim/python.sh isaaclab_arena/evaluation/policy_runner.py \
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python isaaclab_arena/evaluation/policy_runner.py \
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--policy_type rsl_rl \
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--num_steps 1000 \
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--checkpoint_path logs/rsl_rl/generic_experiment/2026-01-28_17-26-10/model_11999.pt \
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.. code-block:: bash
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/isaac-sim/python.sh isaaclab_arena/evaluation/policy_runner.py \
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python isaaclab_arena/evaluation/policy_runner.py \
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--policy_type rsl_rl \
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--num_steps 5000 \
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--num_envs 64 \
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.. code-block:: bash
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/isaac-sim/python.sh isaaclab_arena/evaluation/eval_runner.py --eval_jobs_config eval_config.json
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python isaaclab_arena/evaluation/eval_runner.py --eval_jobs_config eval_config.json
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.. code-block:: text
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