mirror of
https://github.com/jamiepine/voicebox.git
synced 2026-09-15 04:40:40 -07:00
fix: ROCm setup for Linux AMD GPUs (#817)
* Fix ROCm setup for Linux AMD GPUs - Ensure Docker ROCm builds resolve PyTorch packages from the ROCm wheel index so later dependency installs do not replace them with CUDA wheels. - Move ROCm device group handling to a runtime entrypoint that joins the groups owning /dev/kfd and /dev/dri, avoiding distro-specific render/video GID defaults. - Leave HSA_OVERRIDE_GFX_VERSION unset by default in the ROCm compose overlay so newer RDNA GPUs can use native ROCm detection. - Add Linux GPU detection to the Unix setup recipe so AMD systems install ROCm torch wheels and NVIDIA systems install CUDA wheels before backend dependencies. * docs(changelog): add Linux ROCm setup entry * fix(setup): pin ROCm torch wheels and prefer NVIDIA over amdgpu - Install torch/torchaudio from the ROCm index only, before the pooled requirements install, so a plain PyPI (CUDA) wheel can't outrank +rocm - Detect NVIDIA before AMD and gate ROCm on /dev/kfd, so hybrid AMD+NVIDIA hosts get CUDA instead of ROCm
This commit is contained in:
Mike Key
@@ -5,6 +5,17 @@
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# Changelog
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## [Unreleased]
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### Linux
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- **ROCm setup works on Linux AMD systems.** Docker ROCm builds now keep PyTorch
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on the ROCm wheel index during dependency installation, so later installs do
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not replace it with CUDA wheels. The ROCm compose overlay no longer assumes
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Ubuntu render/video group IDs; the container joins the groups that own the GPU
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device nodes at startup. Native Linux setup now picks ROCm wheels for AMD GPUs
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and CUDA wheels for NVIDIA GPUs before installing backend dependencies.
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## [0.5.0] - 2026-04-22
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**The Capture release.** Voicebox stops being just a voice-cloning studio and becomes a full AI voice studio. Hold a key anywhere on your machine, speak, release — the transcript lands in the focused text field. Flip the primitive around and any MCP-aware agent — Claude Code, Cursor, Spacebot — speaks back through an on-screen pill in one of your cloned voices. A local LLM sits between the two, so transcripts come out clean and voice profiles can carry a personality that reshapes what the agent says before it gets spoken.
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+12
-35
@@ -45,18 +45,16 @@ RUN pip install --no-cache-dir --upgrade pip
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COPY backend/requirements.txt .
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# ROCm version to pull PyTorch wheels for. Default is 6.3 (supports RDNA1/2/3).
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# Set ROCM_VERSION=7.2 for RDNA 4 (RX 9000 series) support.
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# ROCm wheel index. Default 6.3 (RDNA1/2/3); set ROCM_VERSION=7.2 for RDNA4.
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ARG ROCM_VERSION=6.3
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# When building the ROCm variant, install the ROCm-enabled PyTorch wheels
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# first so that the subsequent requirements.txt install sees them as already
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# satisfying the torch/torchaudio constraints and leaves them in place.
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# The CPU path skips this step and installs torch from PyPI as before.
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# For ROCm, make the PyTorch ROCm index primary so every install below resolves
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# torch to ROCm wheels instead of the default CUDA build.
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RUN if [ "$PYTORCH_VARIANT" = "rocm" ]; then \
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pip install --no-cache-dir --prefix=/install \
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torch torchaudio \
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--index-url "https://download.pytorch.org/whl/rocm${ROCM_VERSION}"; \
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--index-url "https://download.pytorch.org/whl/rocm${ROCM_VERSION}" \
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torch torchaudio && \
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printf '[global]\nindex-url = https://download.pytorch.org/whl/rocm%s\nextra-index-url = https://pypi.org/simple\n' "$ROCM_VERSION" > /etc/pip.conf; \
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fi
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RUN pip install --no-cache-dir --prefix=/install -r requirements.txt
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@@ -69,37 +67,17 @@ RUN pip install --no-cache-dir --prefix=/install \
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# === Stage 3: Runtime ===
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FROM python:3.11-slim
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# Re-declare ARG inside the stage (Docker scoping requirement).
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ARG PYTORCH_VARIANT=cpu
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# ROCm device access requires the container user to belong to the render
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# and video groups. GIDs are parameterised to match the host; Ubuntu 22.04+
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# defaults are used here. Override via env vars (docker-compose.rocm.yml
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# passes them through automatically):
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# export RENDER_GID=$(getent group render | cut -d: -f3)
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# export VIDEO_GID=$(getent group video | cut -d: -f3)
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ARG RENDER_GID=992
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ARG VIDEO_GID=44
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RUN if [ "$PYTORCH_VARIANT" = "rocm" ]; then \
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groupadd -f -g ${RENDER_GID} render && \
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groupadd -f -g ${VIDEO_GID} video; \
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fi
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# Create non-root user for security
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# Create non-root user; the entrypoint joins GPU device groups at runtime.
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RUN groupadd -r voicebox && \
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useradd -r -g voicebox -m -s /bin/bash voicebox
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# ROCm: add voicebox user to render+video so it can open /dev/kfd and /dev/dri.
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RUN if [ "$PYTORCH_VARIANT" = "rocm" ]; then \
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usermod -aG render,video voicebox; \
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fi
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WORKDIR /app
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# Install only runtime system dependencies
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# Install only runtime system dependencies (gosu drops root in the entrypoint)
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RUN apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg \
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curl \
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gosu \
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&& rm -rf /var/lib/apt/lists/*
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# Copy installed Python packages from builder stage
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@@ -115,9 +93,6 @@ COPY --from=frontend --chown=voicebox:voicebox /build/web/dist /app/frontend/
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RUN mkdir -p /app/data/generations /app/data/profiles /app/data/cache \
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&& chown -R voicebox:voicebox /app/data
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# Switch to non-root user
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USER voicebox
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# Expose the API port
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EXPOSE 17493
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@@ -125,5 +100,7 @@ EXPOSE 17493
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HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=60s \
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CMD curl -f http://localhost:17493/health || exit 1
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# Start the FastAPI server
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# Entrypoint joins GPU groups then drops to the voicebox user
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COPY --chmod=755 scripts/rocm-entrypoint.sh /usr/local/bin/entrypoint.sh
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ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
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CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "17493"]
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+8
-36
@@ -1,24 +1,11 @@
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---
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# ROCm (AMD GPU) overlay for Voicebox
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#
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# Usage:
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# docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
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#
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# Prerequisites on the host:
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# 1. ROCm drivers installed — https://rocm.docs.amd.com/projects/install-on-linux
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# 2. Current user in the 'render' and 'video' groups:
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# sudo usermod -aG render,video $USER (then log out/in)
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#
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# If the render/video GIDs on your host differ from the Ubuntu 22.04 defaults
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# (render=992, video=44), export them before running compose so the build arg
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# and group_add values both stay in sync automatically:
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# export RENDER_GID=$(getent group render | cut -d: -f3)
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# export VIDEO_GID=$(getent group video | cut -d: -f3)
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# docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
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#
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# ROCm version (ROCM_VERSION):
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# Default is 6.3 (supports RDNA1/2/3). For RDNA 4 (RX 9000 series) use 7.2:
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# export ROCM_VERSION=7.2
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# docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
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# Requires ROCm drivers on the host:
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# https://rocm.docs.amd.com/projects/install-on-linux
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# RDNA4 (RX 9000): export ROCM_VERSION=7.2 (default 6.3 covers RDNA1-3).
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services:
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voicebox:
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@@ -26,39 +13,24 @@ services:
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context: .
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args:
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PYTORCH_VARIANT: rocm
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# These build args read from env vars so a single export covers both the
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# Dockerfile group creation and the runtime group_add below.
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RENDER_GID: ${RENDER_GID:-992}
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VIDEO_GID: ${VIDEO_GID:-44}
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ROCM_VERSION: ${ROCM_VERSION:-6.3}
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# Pass the AMD GPU device nodes into the container.
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# /dev/kfd — ROCm compute interface (required for GPU inference)
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# /dev/dri — DRM render nodes (required for display/memory access)
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devices:
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- /dev/kfd
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- /dev/dri
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# Grant access to the render and video groups so the non-root user
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# inside the container can open the GPU device nodes.
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# These reference the same env vars used in build.args above so a
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# single export keeps Dockerfile groups and runtime group_add in sync.
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group_add:
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- "${RENDER_GID:-992}" # render
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- "${VIDEO_GID:-44}" # video
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environment:
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# HSA_OVERRIDE_GFX_VERSION forces the ROCm runtime to treat the GPU as a
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# specific GFX version when auto-detection fails or the GPU is newer than
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# the ROCm release. app.py sets 10.3.0 (RDNA2) by default; override here
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# for your GPU family:
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# RDNA4 / RX 9000 series: 12.0.0 (requires ROCM_VERSION=7.2)
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# RDNA4 / RX 9000 series: 12.0.0
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# (requires ROCM_VERSION=7.2)
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# RDNA3 / RX 7000 series / Strix Halo: 11.0.0
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# RDNA2 / RX 6000 series: 10.3.0
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# RDNA1 / RX 5000 series: 10.1.0
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# Vega / GCN5: 9.0.0
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- HSA_OVERRIDE_GFX_VERSION=11.0.0
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- HSA_OVERRIDE_GFX_VERSION=${HSA_OVERRIDE_GFX_VERSION:-}
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# Tune the ROCm memory allocator to reduce fragmentation during
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# multi-engine inference (TTS + STT + LLM running concurrently).
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# Tune the ROCm memory allocator
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- PYTORCH_HIP_ALLOC_CONF=garbage_collection_threshold:0.8,max_split_size_mb:512
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@@ -43,6 +43,26 @@ setup-python:
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fi
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echo "Installing Python dependencies..."
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{{ pip }} install --upgrade pip -q
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if [ "$(uname)" = "Linux" ]; then
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torch_index=""
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if [ -e /proc/driver/nvidia/version ] || [ -d /sys/module/nvidia ]; then
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echo "Detected NVIDIA GPU — installing CUDA PyTorch..."
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torch_index="https://download.pytorch.org/whl/cu128"
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elif [ -e /dev/kfd ]; then
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if [ -n "${VOICEBOX_ROCM_VERSION:-}" ]; then
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rocm_ver="$VOICEBOX_ROCM_VERSION"
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elif lspci 2>/dev/null | grep -qi "Navi 4"; then
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rocm_ver=7.2
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else
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rocm_ver=6.3
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fi
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echo "Detected AMD GPU — installing ROCm PyTorch (rocm${rocm_ver})..."
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torch_index="https://download.pytorch.org/whl/rocm${rocm_ver}"
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fi
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if [ -n "$torch_index" ]; then
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{{ pip }} install torch torchaudio --index-url "$torch_index"
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fi
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fi
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{{ pip }} install -r {{ backend_dir }}/requirements.txt
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# Chatterbox pins numpy<1.26 / torch==2.6 which break on Python 3.12+
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{{ pip }} install --no-deps chatterbox-tts
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@@ -0,0 +1,15 @@
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#!/bin/sh
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set -e
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# Join whatever groups own the mounted GPU nodes so /dev/kfd and /dev/dri work
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# on any host (no RENDER_GID/VIDEO_GID needed), then drop to the app user.
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for dev in /dev/kfd /dev/dri/render*; do
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[ -e "$dev" ] || continue
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gid=$(stat -c %g "$dev")
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grp=$(getent group "$gid" | cut -d: -f1)
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[ -n "$grp" ] || {
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grp="gpu$gid"
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groupadd -g "$gid" "$grp"
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}
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usermod -aG "$grp" voicebox
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done
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exec gosu voicebox "$@"
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