Summary of this PR:
1. upload DPA-1 related code
2. merge much develop code
3. add all eager composite operators except `softmax_grad`,
`p_norm_grad`, `split_grad`, and `concat_grad` to the composite operator
blacklist(<https://github.com/deepmodeling/deepmd-kit/pull/4414/files#diff-e678abb052b278f8a479f8d13b839a9ec0effd9923478a850bc13758f918e1e9R134-R148>)
to significantly improve model execution speed (reducing the time taken
from 100% more than PyTorch to about 10% to 15% more).
related PR: lanpa/tensorboardX#728
### Training curve:
![training_curves_comparison_eager_opt](https://github.com/user-attachments/assets/3b71fc99-5abf-4353-a61a-38737d3c7f2c)
### Accuracy test(left: paddle, right: torch):
![image](https://github.com/user-attachments/assets/a42b4bfd-c0f8-4eb8-85eb-ff1adf981dbb)
Ralated optimization of Paddle framework:
- [x] PaddlePaddle/Paddle#69349
- [x] PaddlePaddle/Paddle#69333
- [x] PaddlePaddle/Paddle#69479
- [x] PaddlePaddle/Paddle#69515
- [x] PaddlePaddle/Paddle#69487
- [x] PaddlePaddle/Paddle#69661
- [x] PaddlePaddle/Paddle#69660
- [x] PaddlePaddle/Paddle#69596
- [x] PaddlePaddle/Paddle#69556
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
## Release Notes
- **New Features**
- Introduced several new classes for molecular descriptors, including
`DescrptDPA1`, `DescrptBlockSeAtten`, and `LayerNorm`, enhancing the
modeling capabilities for molecular simulations.
- Added new JSON configuration files for model parameters and multitask
models related to water simulations.
- Implemented new test classes for validating the functionality of the
`DPAtomicModel` and various descriptor classes.
- Added new test classes for evaluating denoising models, including
`TestDenoiseModelDPA1` and `TestDenoiseModelDPA2`.
- Enhanced the `ModelWrapper` class to clarify the handling of model
parameters and state management.
- **Bug Fixes**
- Improved internal logic for handling model state saving and loading,
ensuring consistency in outputs.
- **Documentation**
- Enhanced type hints and return annotations across various classes and
methods for better clarity.
- **Tests**
- Expanded the testing framework with new test cases for denoising
models and descriptor functionalities, ensuring robust validation of
features.
- Activated previously skipped tests for energy models, improving test
coverage.
- Enhanced multitask training tests with new configuration handling and
test classes.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Support DPA-2 in paddle backend. This PR will be updated after #4414 is
merged.
### Training curve:
![training_curves_comparison_dpa2](https://github.com/user-attachments/assets/29bdeffa-cf2d-4586-afcf-7df0569997c3)
### Accuracy test(left: paddle, right: torch):
![image](https://github.com/user-attachments/assets/5bff55f3-1c39-4b95-93f0-68783e794716)
Ralated optimization of Paddle framework:
- [x] PaddlePaddle/Paddle#69349
- [x] PaddlePaddle/Paddle#69333
- [x] PaddlePaddle/Paddle#69479
- [x] PaddlePaddle/Paddle#69515
- [x] PaddlePaddle/Paddle#69487
- [x] PaddlePaddle/Paddle#69661
- [x] PaddlePaddle/Paddle#69660
- [x] PaddlePaddle/Paddle#69596
- [x] PaddlePaddle/Paddle#69556
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **New Features**
- Introduced new classes for molecular descriptors: `DescrptDPA2`,
`DescrptBlockRepformers`, `DescrptSeTTebd`, and `DescrptBlockSeTTebd`.
- Added new functions for tensor operations and descriptor management,
enhancing the capabilities of the module.
- Updated JSON configurations for multitask models to refine selection
criteria and data paths.
- **Bug Fixes**
- Improved error handling and parameter validation across various
descriptor classes.
- **Documentation**
- Enhanced test coverage for new descriptor functionalities and
configurations.
- **Tests**
- Added new test classes to validate the functionality of `DescrptDPA2`
and multitask training scenarios.
- Expanded test capabilities for descriptor classes based on installed
dependencies.
- Updated existing tests to support new configurations and
functionalities.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>