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Upstream: https://github.com/michaelgillett/mjlab Upstream-Commit: c19f713c415a699a79d71cd96aa13c3104a05047 Upstream-Branch: main
38 lines
686 B
YAML
38 lines
686 B
YAML
# Example W&B sweep configuration. Customize the task, parameters, and
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# search space for your own experiment.
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#
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# Usage:
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# ./scripts/cloud/sweep-launch.sh A100:4
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name: velocity-lr-entropy-sweep
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project: mjlab
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program: train
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method: random
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metric:
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name: Train/mean_reward
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goal: maximize
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parameters:
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agent.algorithm.learning-rate:
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distribution: log_uniform_values
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min: 1e-4
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max: 1e-2
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agent.algorithm.entropy-coef:
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distribution: log_uniform_values
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min: 0.001
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max: 0.1
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command:
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- ${env}
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- uv
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- run
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- ${program}
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- Mjlab-Velocity-Flat-Unitree-G1
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- --env.scene.num-envs
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- "4096"
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- --agent.max-iterations
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- "6000"
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- ${args}
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run_cap: 8
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