Devcontainers for different AI Applications
Build the base containers:
# at root
# for CPU
docker build -f dev_cpu.dockerfile -t <user>/python:cpu-3.10
# for base GPU (Moslty all use this)
docker build -f dev_gpu.dockerfile -t <user>/python:gpu-3.10
# for dev GPU (Hunyuan3d needs nvcc)
docker build -f dev_gpu.dockerfile --build-arg TAG_LABEL=12.3.1-devel-ubuntu20.04 -t <user>/python:gpu-devel-3.10
then go to any directory in .devcontainer and run docker compose up
.devcontainer for launching debbuger containers with intermediate installation.Number 20
55 commits
Python
98.4%
Dockerfile
1.1%
Devcontainers for different AI Applications
Build the base containers:
# at root
# for CPU
docker build -f dev_cpu.dockerfile -t <user>/python:cpu-3.10
# for base GPU (Moslty all use this)
docker build -f dev_gpu.dockerfile -t <user>/python:gpu-3.10
# for dev GPU (Hunyuan3d needs nvcc)
docker build -f dev_gpu.dockerfile --build-arg TAG_LABEL=12.3.1-devel-ubuntu20.04 -t <user>/python:gpu-devel-3.10
then go to any directory in .devcontainer and run docker compose up
.devcontainer for launching debbuger containers with intermediate installation.Number 20
55 commits
Python
98.4%
Dockerfile
1.1%