Versioning is a crucial aspect of any software development project, including deep learning. It helps in keeping track of changes, managing codebase evolution, and facilitating collaboration among team members. In this section, we'll discuss the importance of versioning and how to implement it effectively in your deep learning project, especially focusing on Git, a widely used version control system.
The main advantages are:
Tracking Changes: Deep learning projects involve multiple iterations and modifications to code, data, and model architectures. Versioning enables you to track these changes over time, providing a clear history of the project's evolution.
Collaboration: When working in a team, versioning allows team members to synchronize their work, merge changes seamlessly, and resolve conflicts efficiently. It promotes collaboration by providing a centralized repository for sharing and reviewing code.
Reproducibility: Versioning ensures reproducibility by preserving the state of the project at different stages. You can always revert to previous versions to reproduce results, debug issues, or experiment with alternative approaches.
Descriptive Commit Messages: Use clear and concise commit messages to describe the changes made in each commit. This helps in understanding the purpose of each change and facilitates collaboration.
Frequent Commits: Commit changes frequently in logical units, rather than making a large number of changes without committing. This ensures granular versioning and simplifies the process of reverting or reviewing changes.
Documentation: Document significant changes, decisions, and dependencies in a README.md file within your repository. This provides context for collaborators and helps newcomers understand the project structure and requirements.
The strategy we will adopt during the thesis is to keep a "main" branch managed by the supervisor and a "develop" branch for the thesis student.
The main branch has to remain clean, all the code in the main branch has to be commented and has to be tested, the main branch has to be a working version of the project.
- Clone project:
git clone <repository-url>-
Branch handling:
- Create a New Branch:
git checkout -b <branch-name>
- Change branch if already created:
git checkout -b <branch-name>
- See all branches:
git branch -a
-
Commit:
- Add changes to commit
git add <file-path>
- Commit changes:
git commit -m "Implemented feature X" -
Push your branch:
git push origin <branch-name>- Delete a branch:
- locally:
git branch -d <branch-name>
- on GitHub:
git push origin --delete <branch-name>