47 lines
1.6 KiB
Docker
47 lines
1.6 KiB
Docker
# Humanoid Skateboarding (mjlab_husky)
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# Ubuntu 22.04 + CUDA 13（训练需 NVIDIA 驱动与 nvidia-container-toolkit）
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#
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# 构建：
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# docker build -t husky-skate:latest .
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#
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# 运行（GPU，Rerun Web）：映射 Web + gRPC 两端口（与终端打印一致）
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# docker run --gpus all -it --rm -p 8080:8080 -p 9876:9876 husky-skate:latest
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#
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# 若宿主机 8080/9876 已被其他容器占用，可换映射（示例 18080/19876）：
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# docker run --gpus all -it --rm -p 18080:18080 -p 19876:19876 husky-skate:latest \
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# uv run play Mjlab-Skater-Flat-Unitree-G1 --checkpoint_file ckpts/test.pt \
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# --viewer rerun --rerun-web-port 18080 --rerun-grpc-port 19876 --no-rerun-open-browser
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#
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# 仅进 shell 调试：
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# docker run --gpus all -it --rm --entrypoint /bin/bash husky-skate:latest
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FROM nvidia/cuda:13.0.1-cudnn-devel-ubuntu22.04
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ENV DEBIAN_FRONTEND=noninteractive \
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PYTHONUNBUFFERED=1 \
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PATH="/root/.local/bin:${PATH}" \
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MUJOCO_GL=egl
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RUN apt-get update && apt-get install -y --no-install-recommends \
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git \
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curl \
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ca-certificates \
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build-essential \
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libgl1 \
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libglib2.0-0 \
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&& rm -rf /var/lib/apt/lists/*
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RUN curl -LsSf https://astral.sh/uv/install.sh | sh
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WORKDIR /app
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COPY . .
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RUN uv sync && uv pip install -e .
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ENV VIRTUAL_ENV=/app/.venv \
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PATH="/app/.venv/bin:${PATH}"
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# 容器内无桌面：默认 Rerun Web；不自动打开浏览器（在宿主机打开终端打印的 URL）
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CMD ["uv", "run", "play", "Mjlab-Skater-Flat-Unitree-G1", "--checkpoint_file", "ckpts/test.pt", "--viewer", "rerun", "--no-rerun-open-browser"]
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