Update M3GNet potential training notebook for the demonstrating of obtaining and using element offset

[kenko911]

Summary

Update M3GNet potential training notebook for the demonstration of obtaining and using element offset

Checklist

• Google format doc strings added. Check with ruff.
• Type annotations included. Check with mypy.
• Tests added for new features/fixes.
• If applicable, new classes/functions/modules have duecredit @due.dcite decorators to reference relevant papers by DOI (example)

Tip: Install pre-commit hooks to auto-check types and linting before every commit:

pip install -U pre-commit
pre-commit install

[coderabbitai]

Walkthrough

Recent changes include enhancements to the PotentialLightningModule constructor in the example notebook, now requiring an element_refs parameter for improved training accuracy. Additionally, sympy version 1.12.1 was added to the requirements.txt to support symbolic computations.

Changes

File	Change Summary
examples/Training a M3GNet Potential with PyTorch Lightning.ipynb	Modified PotentialLightningModule constructor to include element_refs, improving training and validation accuracy.
requirements.txt	Added sympy version 1.12.1 for symbolic computation support.

Sequence Diagram(s)

sequenceDiagram
    participant User
    participant TrainingNotebook
    participant PotentialLightningModule
    participant Model

    User->>TrainingNotebook: Start training
    TrainingNotebook->>PotentialLightningModule: Initialize with model, element_refs, lr, include_line_graph
    PotentialLightningModule->>Model: Setup model with element_refs
    Model-->>PotentialLightningModule: Model ready with element_refs
    PotentialLightningModule-->>TrainingNotebook: Module initialized
    TrainingNotebook-->>User: Training started successfully

Loading

---

Recent review details

Configuration used: .coderabbit.yaml
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 3ac4f39 and 992c17e.

Files selected for processing (1)

• requirements.txt (1 hunks)

Files skipped from review due to trivial changes (1)

• requirements.txt

---

Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?

Share

• X
• Mastodon
• Reddit
• LinkedIn

Tips

Chat

There are 3 ways to chat with CodeRabbit:

• Review comments: Directly reply to a review comment made by CodeRabbit. Example:
  • I pushed a fix in commit <commit_id>.
  • Generate unit testing code for this file.
  • Open a follow-up GitHub issue for this discussion.
• Files and specific lines of code (under the "Files changed" tab): Tag @coderabbitai in a new review comment at the desired location with your query. Examples:
  • @coderabbitai generate unit testing code for this file.
  • @coderabbitai modularize this function.
• PR comments: Tag @coderabbitai in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
  • @coderabbitai generate interesting stats about this repository and render them as a table.
  • @coderabbitai show all the console.log statements in this repository.
  • @coderabbitai read src/utils.ts and generate unit testing code.
  • @coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.
  • @coderabbitai help me debug CodeRabbit configuration file.

Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments.

CodeRabbit Commands (invoked as PR comments)

• @coderabbitai pause to pause the reviews on a PR.
• @coderabbitai resume to resume the paused reviews.
• @coderabbitai review to trigger an incremental review. This is useful when automatic reviews are disabled for the repository.
• @coderabbitai full review to do a full review from scratch and review all the files again.
• @coderabbitai summary to regenerate the summary of the PR.
• @coderabbitai resolve resolve all the CodeRabbit review comments.
• @coderabbitai configuration to show the current CodeRabbit configuration for the repository.
• @coderabbitai help to get help.

Additionally, you can add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.

CodeRabbit Configration File (.coderabbit.yaml)

• You can programmatically configure CodeRabbit by adding a .coderabbit.yaml file to the root of your repository.
• Please see the configuration documentation for more information.
• If your editor has YAML language server enabled, you can add the path at the top of this file to enable auto-completion and validation: # yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json

Documentation and Community

• Visit our Documentation for detailed information on how to use CodeRabbit.
• Join our Discord Community to get help, request features, and share feedback.
• Follow us on X/Twitter for updates and announcements.