ViperEkura
ba8beb81be
- serve.sh/train.sh no longer pass --build on up/run; the build subcommand is the only path that rebuilds - compose services pin image: astrai:latest so run reuses the existing image instead of triggering a rebuild - runtime parsers leave CUDA_VISIBLE_DEVICES unset for gpu.devices: all; an empty string hid every GPU inside the container - server service reserves count: all GPUs so CUDA_VISIBLE_DEVICES performs the only filtering, matching the trainer - wrapper compose() strips an empty host CUDA_VISIBLE_DEVICES before invoking docker compose
98 lines
2.8 KiB
YAML
98 lines
2.8 KiB
YAML
services:
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server:
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image: astrai:latest
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build:
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context: .
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dockerfile: Dockerfile
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args:
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CUDA_TAG: ${CUDA_TAG:-cu128}
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USER_UID: ${ASTRAI_UID:-1000}
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USER_GID: ${ASTRAI_GID:-1000}
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user: "${ASTRAI_UID:-1000}:${ASTRAI_GID:-1000}"
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ports:
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- "${SERVE_PORT:-8000}:${SERVE_CONTAINER_PORT:-8000}"
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volumes:
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- ${SERVE_PARAM_DIR:-./params}:/app/params:ro
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environment:
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- CUDA_VISIBLE_DEVICES
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command: python -m scripts.tools.server --port 8000 --device cuda
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 60s
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restart: unless-stopped
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server-cpu:
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image: astrai:latest
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profiles: [cpu]
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build:
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context: .
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dockerfile: Dockerfile
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args:
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CUDA_TAG: ${CUDA_TAG:-cu128}
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USER_UID: ${ASTRAI_UID:-1000}
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USER_GID: ${ASTRAI_GID:-1000}
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user: "${ASTRAI_UID:-1000}:${ASTRAI_GID:-1000}"
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ports:
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- "${SERVE_PORT:-8000}:${SERVE_CONTAINER_PORT:-8000}"
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volumes:
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- ${SERVE_PARAM_DIR:-./params}:/app/params:ro
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command: python -m scripts.tools.server --port 8000 --device cpu
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 120s
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restart: unless-stopped
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trainer:
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image: astrai:latest
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profiles: [train]
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build:
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context: .
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dockerfile: Dockerfile
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args:
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CUDA_TAG: ${CUDA_TAG:-cu128}
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USER_UID: ${ASTRAI_UID:-1000}
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USER_GID: ${ASTRAI_GID:-1000}
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init: true
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user: "${ASTRAI_UID:-1000}:${ASTRAI_GID:-1000}"
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volumes:
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- ${TRAIN_DATA_DIR:-./data}:/data:ro
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- ${TRAIN_MODEL_DIR:-./params}:/models/base:ro
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- ${TRAIN_CHECKPOINT_DIR:-./checkpoints}:/checkpoints
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environment:
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- TRAIN_JOB_NAME=${TRAIN_JOB_NAME:-astrai-train}
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- TRAIN_CONFIG=${TRAIN_CONFIG:-}
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- BASE_MODEL=${BASE_MODEL:-/models/base}
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- CHECKPOINT_ROOT=/checkpoints
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- TRAIN_GPU_COUNT=${TRAIN_GPU_COUNT:-all}
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- TRAIN_PARALLEL_MODE=${TRAIN_PARALLEL_MODE:-auto}
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- CUDA_VISIBLE_DEVICES
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entrypoint: ["bash", "/app/scripts/docker/train-entrypoint.sh"]
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ipc: ${TRAIN_IPC_MODE:-host}
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stop_grace_period: ${TRAIN_STOP_GRACE_PERIOD:-10m}
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restart: "no"
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logging:
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driver: json-file
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options:
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max-size: ${TRAIN_LOG_MAX_SIZE:-100m}
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max-file: ${TRAIN_LOG_MAX_FILES:-5}
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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