deepmodeling / deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics
https://docs.deepmodeling.com/projects/deepmd/
GNU Lesser General Public License v3.0
1.41k stars 487 forks source link

refactor: remove global data_requirements #3798

Closed njzjz closed 1 month ago

njzjz commented 1 month ago

Fix #3522. Fix #3540.

Summary by CodeRabbit

coderabbitai[bot] commented 1 month ago
Walkthrough ## Walkthrough The recent changes refactor the handling of data requirements in the `deepmd` library to eliminate the use of global variables. This involves removing the `data_requirement` global variable, introducing `DataRequirementItem`, and adding properties like `input_requirement` and `label_requirement` to manage data requirements within classes. This refactor aims to enhance modularity and maintainability by encapsulating data requirements within relevant classes. ## Changes | Files/Modules | Change Summary | |---------------|----------------| | `source/tests/pt/model/test_model.py` | Removed `data_requirement` import, added `dp_ds.add_data_requirements(dp_model.input_requirement)`, and removed `data.add_dict(data_requirement)`. | | `deepmd/utils/data_system.py` | Removed `data_requirement` import, added `DataRequirementItem` import, modified `add_dict` method, added `add_data_requirements` method. | | `deepmd/tf/common.py` | Removed `data_requirement` global variable and `add_data_requirement` function. | | `deepmd/tf/descriptor/descriptor.py` | Added `DataRequirementItem` import, introduced `input_requirement` property. | | `deepmd/tf/descriptor/se_a_ebd.py` | Removed `add_data_requirement` import, added `DataRequirementItem` import, refactored data requirement handling in `__init__` and added `input_requirement` property. | | `deepmd/tf/descriptor/se_a_ef.py` | Removed `add_data_requirement` import, added `DataRequirementItem` import, refactored data requirement handling in `__init__` and added `input_requirement` property. | | `deepmd/tf/entrypoints/train.py` | Updated `_do_work` function to add data requirements to training and validation data objects. | | `deepmd/tf/fit/dos.py`, `deepmd/tf/fit/ener.py` | Removed `add_data_requirement` calls, introduced `input_requirement` property. | | `deepmd/tf/fit/fitting.py` | Added `DataRequirementItem` import, introduced `input_requirement` property. | | `deepmd/tf/loss/dos.py`, `deepmd/tf/loss/ener.py`, `deepmd/tf/loss/loss.py`, `deepmd/tf/loss/tensor.py` | Removed `add_data_requirement` calls, introduced `label_requirement` property. | | `deepmd/tf/model/frozen.py`, `deepmd/tf/model/linear.py`, `deepmd/tf/model/model.py`, `deepmd/tf/model/pairtab.py`, `deepmd/tf/model/pairwise_dprc.py` | Added `DataRequirementItem` import, introduced `input_requirement` property. | | `deepmd/tf/train/trainer.py` | Removed `data_requirement` import, added `DataRequirementItem` import, refactored `_build_network` method, added `data_requirements` property. | | `source/tests/tf/test_data_modifier.py`, `source/tests/tf/test_data_modifier_shuffle.py` | Replaced `data_requirement` with `model.data_requirements`. | | `deepmd/utils/data.py` | Added `__eq__` and `__repr__` methods to `DataRequirementItem`. | | `source/tests/tf/test_loss_gf.py`, `source/tests/tf/test_model_se_a.py`, `source/tests/tf/test_model_se_a_aparam.py`, `source/tests/tf/test_model_se_a_fparam.py`, `source/tests/tf/test_pairwise_dprc.py` | Added tests for `DataRequirementItem` and input requirements. | ## Assessment against linked issues | Objective | Addressed | Explanation | |-----------|-----------|-------------| | Refactor `data_requirement` to not be a global variable (#3522) | ✅ | | | Remove line when `data_requirement` is not a global variable (#3540) | ✅ | | Overall, the changes effectively address the objectives outlined in the linked issues by refactoring the handling of data requirements to eliminate global variables and improve encapsulation within the relevant classes.

Recent Review Details **Configuration used: CodeRabbit UI** **Review profile: CHILL**
Commits Files that changed from the base of the PR and between 15db5df823c75759a8db7b6902a28787ff7c93ec and 126295b49a29368ae2ff0c836c7b7f2cd665e52a.
Files selected for processing (6) * deepmd/utils/data.py (1 hunks) * source/tests/tf/test_loss_gf.py (2 hunks) * source/tests/tf/test_model_se_a.py (1 hunks) * source/tests/tf/test_model_se_a_aparam.py (2 hunks) * source/tests/tf/test_model_se_a_fparam.py (2 hunks) * source/tests/tf/test_pairwise_dprc.py (2 hunks)
Files skipped from review due to trivial changes (1) * source/tests/tf/test_pairwise_dprc.py
Additional comments not posted (8)
source/tests/tf/test_loss_gf.py (2)
`8-10`: LGTM! The import of `DataRequirementItem` aligns with the refactoring to handle data requirements locally. --- `32-86`: Excellent addition of `test_label_requirements`. This test method effectively checks the correctness of the `label_requirement` property, ensuring it meets the new data handling requirements.
source/tests/tf/test_model_se_a_aparam.py (2)
`19-21`: LGTM! The import of `DataRequirementItem` is necessary for the new data requirement handling. --- `172-176`: Excellent addition of a test to verify the `input_requirement` for `aparam`. This ensures that the model's data requirements are correctly implemented and tested.
source/tests/tf/test_model_se_a_fparam.py (2)
`19-21`: LGTM! The import of `DataRequirementItem` is necessary for the new data requirement handling. --- `173-180`: Excellent addition of a test to verify the `input_requirement` for `fparam`. This ensures that the model's data requirements are correctly implemented and tested.
source/tests/tf/test_model_se_a.py (1)
`268-270`: Good addition of a test to verify the `input_requirement` for the model. This ensures that the model's data requirements are correctly implemented and tested, even if it expects no specific requirements.
deepmd/utils/data.py (1)
`796-797`: Review the representation method `__repr__`. The `__repr__` method provides a clear and concise string representation of the object, which is useful for debugging and logging.
--- 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](https://twitter.com/intent/tweet?text=I%20just%20used%20%40coderabbitai%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20the%20proprietary%20code.%20Check%20it%20out%3A&url=https%3A//coderabbit.ai) - [Mastodon](https://mastodon.social/share?text=I%20just%20used%20%40coderabbitai%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20the%20proprietary%20code.%20Check%20it%20out%3A%20https%3A%2F%2Fcoderabbit.ai) - [Reddit](https://www.reddit.com/submit?title=Great%20tool%20for%20code%20review%20-%20CodeRabbit&text=I%20just%20used%20CodeRabbit%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20proprietary%20code.%20Check%20it%20out%3A%20https%3A//coderabbit.ai) - [LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fcoderabbit.ai&mini=true&title=Great%20tool%20for%20code%20review%20-%20CodeRabbit&summary=I%20just%20used%20CodeRabbit%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20proprietary%20code)
Tips ### Chat There are 3 ways to chat with [CodeRabbit](https://coderabbit.ai): - Review comments: Directly reply to a review comment made by CodeRabbit. Example: - `I pushed a fix in commit .` - `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.` 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 a review. This is useful when automatic reviews are disabled for the repository. - `@coderabbitai resolve` resolve all the CodeRabbit review comments. - `@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](https://docs.coderabbit.ai/guides/configure-coderabbit) 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](https://coderabbit.ai/docs) for detailed information on how to use CodeRabbit. - Join our [Discord Community](https://discord.com/invite/GsXnASn26c) to get help, request features, and share feedback. - Follow us on [X/Twitter](https://twitter.com/coderabbitai) for updates and announcements.
codecov[bot] commented 1 month ago

Codecov Report

Attention: Patch coverage is 75.53957% with 34 lines in your changes are missing coverage. Please review.

Project coverage is 82.56%. Comparing base (81b5949) to head (126295b).

Files Patch % Lines
deepmd/tf/model/frozen.py 27.27% 8 Missing :warning:
deepmd/tf/fit/dos.py 33.33% 6 Missing :warning:
deepmd/tf/loss/ener.py 80.64% 6 Missing :warning:
deepmd/tf/descriptor/se_a_ebd.py 42.85% 4 Missing :warning:
deepmd/tf/loss/dos.py 50.00% 4 Missing :warning:
deepmd/tf/descriptor/se_a_ef.py 50.00% 3 Missing :warning:
deepmd/tf/model/linear.py 80.00% 1 Missing :warning:
deepmd/tf/model/pairtab.py 75.00% 1 Missing :warning:
deepmd/utils/data.py 83.33% 1 Missing :warning:
Additional details and impacted files ```diff @@ Coverage Diff @@ ## devel #3798 +/- ## ========================================== - Coverage 82.58% 82.56% -0.03% ========================================== Files 515 515 Lines 48806 48899 +93 Branches 2982 2983 +1 ========================================== + Hits 40308 40373 +65 - Misses 7587 7615 +28 Partials 911 911 ```

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.