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Upstream: https://github.com/michaelgillett/mjlab Upstream-Commit: c19f713c415a699a79d71cd96aa13c3104a05047 Upstream-Branch: main
45 lines
969 B
YAML
45 lines
969 B
YAML
# SkyPilot task for launching mjlab training on Lambda Cloud.
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#
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# Installs mjlab directly with uv (no Docker).
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#
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# Usage:
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# sky launch scripts/cloud/train.yaml \
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# --env TASK=Mjlab-Velocity-Flat-Unitree-G1
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name: mjlab-train
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resources:
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cloud: lambda
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accelerators: A100:1
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autostop:
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idle_minutes: 5
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down: true
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workdir: .
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file_mounts:
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~/.netrc: ~/.netrc
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envs:
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TASK: Mjlab-Velocity-Flat-Unitree-G1
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NUM_ENVS: "4096"
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MAX_ITERATIONS: "6000"
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MUJOCO_GL: egl
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setup: |
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# Install EGL for MuJoCo headless rendering.
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sudo apt-get update && sudo apt-get install -y libegl-dev
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# Install uv if not present.
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command -v uv || curl -LsSf https://astral.sh/uv/install.sh | sh
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source "$HOME/.local/bin/env" 2>/dev/null || true
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uv sync --locked --no-dev
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run: |
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source "$HOME/.local/bin/env" 2>/dev/null || true
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uv run train "$TASK" \
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--env.scene.num-envs "$NUM_ENVS" \
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--agent.max-iterations "$MAX_ITERATIONS" \
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--gpu-ids all
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