fix(docker): add ROCm GPU support via compose overlay (#630)

* fix(docker): add ROCm GPU support via compose overlay

Fixes #618. The Docker image installs CPU-only PyTorch from PyPI by
default, so even when users correctly pass /dev/kfd and /dev/dri device
nodes into the container, torch.cuda.is_available() returns False and
the GPU is reported as "None (CPU only)".

Changes:
- Dockerfile: add PYTORCH_VARIANT build arg (default: cpu). When set to
  "rocm", the ROCm-enabled PyTorch wheels are installed from the
  pytorch.org/whl/rocm6.3 index before requirements.txt runs, so pip
  sees the ROCm build as already satisfying the torch>=2.2.0 constraint
  and does not overwrite it with the CPU wheel. The render and video
  groups are created with parameterised GIDs (RENDER_GID / VIDEO_GID,
  defaulting to Ubuntu 22.04 values) and the voicebox user is added to
  both groups so it can open /dev/kfd and /dev/dri.

- docker-compose.rocm.yml: new compose overlay that wires everything
  together — PYTORCH_VARIANT=rocm build arg, /dev/kfd + /dev/dri device
  passthrough, group_add for render/video, HSA_OVERRIDE_GFX_VERSION
  (defaults to 11.0.0 for RDNA3/Strix Halo with a comment listing
  values for RDNA2/RDNA1/Vega), and PYTORCH_HIP_ALLOC_CONF for the
  memory allocator. Usage:
    docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build

- docker-compose.yml: add a comment pointing to the ROCm overlay.

The CPU default path is unchanged — no extra build time, no size increase.

Co-authored-by: Cursor <[email protected]>

* fix(docker): address review comments on ROCm overlay

Two issues raised in PR review:

1. CodeRabbit: `docker compose up --build-arg` is not supported by the
   `up` subcommand. Replaced the GID override instructions with the
   correct env-var export pattern. Added RENDER_GID and VIDEO_GID to
   `build.args` using ${VAR:-default} interpolation so a single export
   covers both the Dockerfile group creation and the runtime group_add.
   Changed group_add entries from hardcoded strings to the same
   interpolated vars so host GIDs stay in sync end-to-end.

2. @Xarianne: ROCm 6.3 does not support RDNA 4 (RX 9000 series) cards.
   Added a ROCM_VERSION build arg (default 6.3) to both the Dockerfile
   and docker-compose.rocm.yml so users can set ROCM_VERSION=7.2 for
   RDNA 4 support without editing any files. Added RDNA 4 / 12.0.0 to
   the HSA_OVERRIDE_GFX_VERSION comment table.

Co-authored-by: Cursor <[email protected]>

---------

Co-authored-by: Cursor <[email protected]>

docker-compose.rocm.yml

@@ -0,0 +1,64 @@
+# ROCm (AMD GPU) overlay for Voicebox
+#
+# Usage:
+#   docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
+#
+# Prerequisites on the host:
+#   1. ROCm drivers installed — https://rocm.docs.amd.com/projects/install-on-linux
+#   2. Current user in the 'render' and 'video' groups:
+#        sudo usermod -aG render,video $USER   (then log out/in)
+#
+# If the render/video GIDs on your host differ from the Ubuntu 22.04 defaults
+# (render=992, video=44), export them before running compose so the build arg
+# and group_add values both stay in sync automatically:
+#   export RENDER_GID=$(getent group render | cut -d: -f3)
+#   export VIDEO_GID=$(getent group video  | cut -d: -f3)
+#   docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
+#
+# ROCm version (ROCM_VERSION):
+#   Default is 6.3 (supports RDNA1/2/3). For RDNA 4 (RX 9000 series) use 7.2:
+#   export ROCM_VERSION=7.2
+#   docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
+
+services:
+  voicebox:
+    build:
+      context: .
+      args:
+        PYTORCH_VARIANT: rocm
+        # These build args read from env vars so a single export covers both the
+        # Dockerfile group creation and the runtime group_add below.
+        RENDER_GID: ${RENDER_GID:-992}
+        VIDEO_GID: ${VIDEO_GID:-44}
+        ROCM_VERSION: ${ROCM_VERSION:-6.3}
+
+    # Pass the AMD GPU device nodes into the container.
+    # /dev/kfd  — ROCm compute interface (required for GPU inference)
+    # /dev/dri  — DRM render nodes (required for display/memory access)
+    devices:
+      - /dev/kfd
+      - /dev/dri
+
+    # Grant access to the render and video groups so the non-root user
+    # inside the container can open the GPU device nodes.
+    # These reference the same env vars used in build.args above so a
+    # single export keeps Dockerfile groups and runtime group_add in sync.
+    group_add:
+      - "${RENDER_GID:-992}"   # render
+      - "${VIDEO_GID:-44}"     # video
+
+    environment:
+      # HSA_OVERRIDE_GFX_VERSION forces the ROCm runtime to treat the GPU as a
+      # specific GFX version when auto-detection fails or the GPU is newer than
+      # the ROCm release. app.py sets 10.3.0 (RDNA2) by default; override here
+      # for your GPU family:
+      #   RDNA4 / RX 9000 series:              12.0.0  (requires ROCM_VERSION=7.2)
+      #   RDNA3 / RX 7000 series / Strix Halo: 11.0.0
+      #   RDNA2 / RX 6000 series:              10.3.0
+      #   RDNA1 / RX 5000 series:              10.1.0
+      #   Vega / GCN5:                          9.0.0
+      - HSA_OVERRIDE_GFX_VERSION=11.0.0
+
+      # Tune the ROCm memory allocator to reduce fragmentation during
+      # multi-engine inference (TTS + STT + LLM running concurrently).
+      - PYTORCH_HIP_ALLOC_CONF=garbage_collection_threshold:0.8,max_split_size_mb:512