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docker-compose.test.yml
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docker-compose.test.yml
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version: "3.9"
services:
web:
build:
context: .
dockerfile: ./Dockerfile
command:
- uvicorn
- api:main
- --host=0.0.0.0
- --workers=2
- --reload
ports:
- 8000:8000
volumes:
- type: bind
source: ./
target: /app/
- type: bind
source: ./data/
target: /data/
read_only: true
restart: on-failure
tfserving:
image: tensorflow/serving:2.5.1-gpu
runtime: nvidia
shm_size: '1gb'
command:
- --model_name=resnet_50_classification
- --model_base_path=/models/
- --max_num_load_retries=0
- --file_system_poll_wait_seconds=0
- --enable_model_warmup=true
- --per_process_gpu_memory_fraction=1.0
- --flush_filesystem_caches=false
- --load_retry_interval_micros=-1
- --model_config_file_poll_wait_seconds=0
- --port=9000
- --rest_api_port=8501
volumes:
- type: bind
source: ./models/tfserving/
target: /models/
read_only: true
ports:
- 8501:8501
- 9000:9000
restart: on-failure
torchserve:
image: pytorch/torchserve:0.4.0-gpu
runtime: nvidia
shm_size: '1gb'
command:
- torchserve
- --model-store=/models/
- --start
- --foreground
- --models=all
- --ts-config=/configuration/config.properties
volumes:
- type: bind
source: ./models/torchserve/
target: /models/
read_only: true
- type: bind
source: ./configuration/torchserve/config.properties
target: /configuration/config.properties
read_only: true
ports:
- 8080:8080
- 7070:7070
restart: on-failure
triton:
# This is compatible with the latest DLAMI
# https://docs.nvidia.com/deeplearning/triton-inference-server/release-notes/rel_20-09.html#rel_20-09
image: nvcr.io/nvidia/tritonserver:20.10-py3
runtime: nvidia
shm_size: '1gb'
command:
- tritonserver
- --model-repository=/models
- --model-control-mode=none
- --allow-grpc=true
- --allow-http=true
- --log-verbose=true
- --log-info=true
- --log-warning=true
- --log-error=true
- --exit-on-error=true
- --strict-model-config=true
- --strict-readiness=true
- --exit-timeout-secs=10
ports:
- 8000:8000
- 8001:8001
volumes:
- type: bind
source: ./models/triton/
target: /models/
read_only: true
restart: on-failure