[API] Optimize paddle.where and paddle.where_ in eager mode
#69556
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zyfncg
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Nov 22, 2024
python/paddle/tensor/search.py
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| broadcast_shape = paddle.broadcast_shape(x_shape, y_shape) | ||
| broadcast_shape = paddle.broadcast_shape(broadcast_shape, condition_shape) | ||
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| broadcast_x = x | ||
| broadcast_y = y | ||
| broadcast_condition = condition | ||
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| if condition_shape != broadcast_shape: | ||
| broadcast_condition = paddle.broadcast_to( | ||
| broadcast_condition, broadcast_shape | ||
| ) | ||
| if x_shape != broadcast_shape: | ||
| broadcast_x = paddle.broadcast_to(broadcast_x, broadcast_shape) | ||
| if y_shape != broadcast_shape: | ||
| broadcast_y = paddle.broadcast_to(broadcast_y, broadcast_shape) |
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确认下broadcast_shape和broadcast_to是否支持动态shape, 不支持的话静态图下可能会有问题
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确认下broadcast_shape和broadcast_to是否支持动态shape, 不支持的话静态图下可能会有问题
看了下，修改前的代码用了add这个支持动态shape的算子进行了隐式broadcast，所以静态图支持动态shape，但是修改之后的方案依赖于broadcast_shape和broadcast_to，这两个算子至少有一个存在对-1的处理BUG，导致静态图下的运行时结果不太对，所以目前的临时解决方案是：新的代码逻辑放在dynamic_mode里面，pir仍然使用原本来的代码。这样不影响已有功能。
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paddle.where and paddle.where_ in eager mode
zyfncg
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Nov 22, 2024
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zyfncg
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Nov 28, 2024
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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:  ### Accuracy test(left: paddle, right: torch):  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>
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Support DPA-2 in paddle backend. This PR will be updated after #4414 is merged. ### Training curve:  ### Accuracy test(left: paddle, right: torch):  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>
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PR Category
Performance Optimization
PR Types
Improvements
Description
Pcard-75624
paddle.where和paddle.where_的原有实现通过多次调用基础二元运算符进行隐式广播，从而让cond,x,,y形状保持一致，优化之后使用无计算量的broadcast_shape计算广播后的形状，再使用broadcast_to进行广播，极大简化了代码逻辑，并且减少了不必要的前向和反向算子开销where_部分动态图单测，并且修复了个别静态图单测中，占位符形状和实际数据形状不一致的问题。Note
考虑到broadcast_shape和broadcast_to暂时没有完全适配动态shape，因此本PR只针对动态图分支进行修改