[fix bug] load atomic_*.npy for tf tensor model #4538

ChiahsinChu · 2025-01-06T12:17:45Z

Fix bug mentioned in #4536

Summary by CodeRabbit

Bug Fixes
- Updated atomic property and weight label naming conventions across the machine learning training and loss components to ensure consistent terminology.
- Corrected placeholder key references in the training process to match updated label names.

coderabbitai · 2025-01-06T12:20:51Z

📝 Walkthrough

Walkthrough

The pull request involves modifications to two files in the deepmd library, focusing on terminology changes related to atomic properties and placeholders. In deepmd/tf/loss/tensor.py, the label naming convention for atomic properties and weights is updated from "atom_" to "atomic_". Correspondingly, in deepmd/tf/train/trainer.py, a transformation is applied to the self.place_holders dictionary, converting "atomic_" keys back to "atom_" keys during the training process.

Changes

File	Change Summary
`deepmd/tf/loss/tensor.py`	- Updated label naming from `"atom_" + self.label_name` to `"atomic_" + self.label_name` - Changed `"atom_weight"` to `"atomic_weight"` in `label_requirement` method
`deepmd/tf/train/trainer.py`	- Modified `self.place_holders` dictionary keys - Replaced "atomic_" substring with "atom_" in placeholder keys

Sequence Diagram

sequenceDiagram
    participant Loss as TensorLoss
    participant Trainer as DPTrainer
    
    Loss ->> Loss: Update label naming
    Note over Loss: Change "atom_" to "atomic_"
    
    Trainer ->> Trainer: Transform placeholders
    Note over Trainer: Convert "atomic_" back to "atom_"

The sequence diagram illustrates the key transformations in the label and placeholder naming conventions, showing how the changes are applied in the loss and training components.

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

🪧 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>, please review it.
- 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 gather interesting stats about this repository and render them as a table. Additionally, render a pie chart showing the language distribution in the codebase.
- @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 using 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 generate docstrings to generate docstrings for this PR. (Beta)
@coderabbitai resolve resolve all the CodeRabbit review comments.
@coderabbitai configuration to show the current CodeRabbit configuration for the repository.
@coderabbitai help to get help.

Other keywords and placeholders

Add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.
Add @coderabbitai summary to generate the high-level summary at a specific location in the PR description.
Add @coderabbitai anywhere in the PR title to generate the title automatically.

CodeRabbit Configuration 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.

coderabbitai

Actionable comments posted: 1

📜 Review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 8d4c27b and e214ee9.

📒 Files selected for processing (2)

deepmd/tf/loss/tensor.py (2 hunks)
deepmd/tf/train/trainer.py (1 hunks)

⏰ Context from checks skipped due to timeout of 90000ms (4)

GitHub Check: Build C library (2.14, >=2.5.0rc0,<2.15, libdeepmd_c_cu11.tar.gz)
GitHub Check: Test C++ (false)
GitHub Check: Build C library (2.18, libdeepmd_c.tar.gz)
GitHub Check: Test C++ (true)

🔇 Additional comments (2)

deepmd/tf/loss/tensor.py (1)

158-158: Confirm consistency with renamed placeholders.
You've updated "atom_" + self.label_name to "atomic_" + self.label_name. However, in trainer.py, placeholders are renamed from "atomic_" back to "atom_". Ensure that the rest of the code consistently references the updated label to avoid key mismatches.

deepmd/tf/train/trainer.py (1)

284-290: Verify potential placeholder mismatch.
This loop renames all placeholders from "atomic_" to "atom_", which seemingly contradicts the new naming convention in tensor.py. Please verify that any references to "atomic_*" placeholders still function correctly after this transformation, and confirm that this rename is truly intended.

deepmd/tf/loss/tensor.py

codecov · 2025-01-06T13:10:49Z

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 84.57%. Comparing base (8d4c27b) to head (e214ee9).
Report is 73 commits behind head on devel.

Additional details and impacted files

@@            Coverage Diff             @@
##            devel    #4538      +/-   ##
==========================================
- Coverage   84.57%   84.57%   -0.01%     
==========================================
  Files         675      675              
  Lines       63695    63698       +3     
  Branches     3488     3486       -2     
==========================================
+ Hits        53872    53874       +2     
  Misses       8698     8698              
- Partials     1125     1126       +1

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.
📦 JS Bundle Analysis: Save yourself from yourself by tracking and limiting bundle sizes in JS merges.

Fix bug mentioned in deepmodeling#4536  - **Bug Fixes** - Updated atomic property and weight label naming conventions across the machine learning training and loss components to ensure consistent terminology. - Corrected placeholder key references in the training process to match updated label names.  (cherry picked from commit 380efb9)

fix bug in tf tensor loss

e214ee9

github-actions bot added the Python label Jan 6, 2025

coderabbitai bot reviewed Jan 6, 2025

View reviewed changes

deepmd/tf/loss/tensor.py Show resolved Hide resolved

njzjz linked an issue Jan 6, 2025 that may be closed by this pull request

[BUG] (tf backend) Print NAN when training dipole model with reference data #4536

Closed

njzjz approved these changes Jan 6, 2025

View reviewed changes

wanghan-iapcm added this pull request to the merge queue Jan 7, 2025

Merged via the queue into deepmodeling:devel with commit 380efb9 Jan 7, 2025
61 checks passed

njzjz added this to the v3.0.2 milestone Feb 9, 2025

anyangml mentioned this pull request Feb 18, 2025

[BUG] Atom vs Atomic problem marked as solved in #4536 still a problem #4601

Closed

coderabbitai bot mentioned this pull request Mar 4, 2025

feat(pt): add atomic_weight to dipole model inference #4628

Closed

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Uh oh!

[fix bug] load atomic_*.npy for tf tensor model #4538

[fix bug] load atomic_*.npy for tf tensor model #4538

Uh oh!

ChiahsinChu commented Jan 6, 2025 •

edited by coderabbitai bot

Loading

Uh oh!

coderabbitai bot commented Jan 6, 2025

Walkthrough

Changes

Sequence Diagram

Chat

CodeRabbit Commands (Invoked using PR comments)

Other keywords and placeholders

CodeRabbit Configuration File (`.coderabbit.yaml`)

Documentation and Community

Uh oh!

coderabbitai bot left a comment

Uh oh!

Uh oh!

codecov bot commented Jan 6, 2025 •

edited

Loading

Uh oh!

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

3 participants

[fix bug] load atomic_*.npy for tf tensor model #4538

[fix bug] load atomic_*.npy for tf tensor model #4538

Uh oh!

Conversation

ChiahsinChu commented Jan 6, 2025 • edited by coderabbitai bot Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Summary by CodeRabbit

Uh oh!

coderabbitai bot commented Jan 6, 2025

Walkthrough

Changes

Sequence Diagram

Chat

CodeRabbit Commands (Invoked using PR comments)

Other keywords and placeholders

CodeRabbit Configuration File (.coderabbit.yaml)

Documentation and Community

Uh oh!

coderabbitai bot left a comment

Choose a reason for hiding this comment

Uh oh!

Uh oh!

codecov bot commented Jan 6, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Codecov Report

Uh oh!

Uh oh!

Reviewers

Assignees

Labels

Projects

Milestone

Development

Uh oh!

3 participants

ChiahsinChu commented Jan 6, 2025 •

edited by coderabbitai bot

Loading

CodeRabbit Configuration File (`.coderabbit.yaml`)

codecov bot commented Jan 6, 2025 •

edited

Loading