Minimal sleap-nn CUDA Base Image - #23
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Pull Request Overview
This PR establishes a production-ready Docker-based development environment for the sleap-nn project with CUDA 12.8 support. It introduces comprehensive CI/CD automation to build and publish GPU-enabled container images.
Key Changes:
- Production Dockerfile with NVIDIA CUDA 12.8, Python 3.13, and sleap-nn installation
- Dual GitHub Actions workflows for automated image builds (production and test branches)
- VS Code devcontainer configuration for local GPU-enabled development
Reviewed Changes
Copilot reviewed 5 out of 6 changed files in this pull request and generated 5 comments.
Show a summary per file
| File | Description |
|---|---|
| sleapnn_v002_cuda_v128/Dockerfile | Builds GPU-enabled container with CUDA 12.8, Python 3.13, and sleap-nn package |
| sleapnn_v002_cuda_v128/.dockerignore | Excludes build artifacts and version control files from Docker context |
| sleapnn_v002_cuda_v128/.devcontainer/devcontainer.json | Configures VS Code development container with GPU access |
| .github/workflows/sleap_nn_v002_cuda_test.yml | Builds and pushes test Docker images for non-main branches with -test tags |
| .github/workflows/sleap_nn_v002_cuda_production.yml | Builds and pushes production Docker images for main branch |
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eberrigan
approved these changes
Oct 21, 2025
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
eberrigan
reviewed
Oct 23, 2025
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| - The `ghcr.io/talmolab/sleap-rtc-worker` is the Docker registry where the images are pulled from. This is only used when pulling images from the cloud, and not necesary when building/running locally. |
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| ## Contributing | ||
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| - Use the `devcontainer.json` to open the repo in a dev container using VS Code. |
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is this up-to-date for this devcontainer?
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This pull request introduces a new development environment for the
sleapnn_v002_cuda_v128project, including a production-ready Dockerfile with CUDA 12.8 support, a devcontainer configuration for VS Code, and two new GitHub Actions workflows for building and pushing Docker images (for both production and test).Notes:
Dockerfileinsleapnn_v002_cuda_v128to build a GPU-enabled container using CUDA 12.8, Python 3.13, and thesleap-nnpackage with CUDA support, along with a virtual environment setup and necessary dependencies..devcontainer/devcontainer.jsonfor VS Code development containers, enabling GPU access and customizing the development environment for easier local development and debugging..dockerignorefile to exclude unnecessary files and directories from Docker build context, improving build efficiency..github/workflows/sleap_nn_v002_cuda_production.ymlto build and push production Docker images to GitHub Container Registry when changes are pushed tomainor the workflow file itself. The workflow tags images with multiple relevant tags for versioning and traceability..github/workflows/sleap_nn_v002_cuda_test.ymlto build and push test Docker images (with-testtags) for branches other thanmain, including a step to free up disk space on the runner for more reliable builds.