58e15fe10f | ||
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.. | ||
install | ||
Dockerfile.ci_cpu | ||
Dockerfile.ci_emscripten | ||
Dockerfile.ci_gpu | ||
Dockerfile.ci_i386 | ||
Dockerfile.ci_jekyll | ||
Dockerfile.ci_lint | ||
Dockerfile.demo_android | ||
Dockerfile.demo_cpu | ||
Dockerfile.demo_gpu | ||
Dockerfile.demo_opencl | ||
README.md | ||
bash.sh | ||
build.sh | ||
with_the_same_user |
README.md
TVM Docker
This directory contains the TVM's docker infrastructure. We use docker to provide build environments for CI and images for demo. We need docker and nvidia-docker for GPU images.
Start Docker Bash Session
You can use the following helper script to start an interactive bash session with a given image_name.
/path/to/tvm/docker/bash.sh image_name
The script does the following things:
- Mount current directory to /workspace and set it as home
- Switch user to be the same user that calls the bash.sh
- Use the host-side network
The helper bash script can be useful to build demo sessions.
Prebuilt Docker Images
We provide several pre-built images for doing quick exploration with TVM installed.
For example, you can run the following command to get tvmai/demo-cpu
image.
/path/to/tvm/docker/bash.sh tvmai/demo-cpu
Then inside the docker container, you can type the following command to start the jupyter notebook
jupyter notebook
Check out https://hub.docker.com/r/tvmai/ to get the full list of available prebuilt images.
Use Local Build Script
We also provide script to build docker images locally.
We use (build.sh
)[./build.sh] to build and run the commands.
To build and run docker images, we can run the following command
at the root of the project.
./docker/build.sh image_name [command]
Here image_name corresponds to the docker defined in the
Dockerfile.image_name
.
You can also start an interactive session by typing
./docker/build.sh image_name -it bash
The build command will map the tvm root to /workspace/ inside the container with the same user as the user invoking the docker command. Here are some common use examples to perform CI tasks.
-
lint the python codes
./docker/build.sh ci_lint make pylint
-
build codes with CUDA support
./docker/build.sh ci_gpu make -j$(nproc)
-
do the python unittest
./docker/build.sh ci_gpu tests/scripts/task_python_unittest.sh
-
build the documents. The results will be available at
docs/_build/html
./docker/ci_build.sh ci_gpu make -C docs html
-
build golang test suite.
./docker/build.sh ci_cpu tests/scripts/task_golang.sh