[CINN]Delete shape_optimization flag And Refine ApplyCinnPass #70947
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gongshaotian
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Hongqing-work
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We verified paddle CINN compiler in DPA-2 example(single A100-SXM (40G), cada11.8, Intel(R) Xeon(R) Gold 6248 CPU @ 2.50GHz x 160). To enable CINN compiler in training, add one flag: `CINN=1` before training command, e.g. `CINN=1 dp --pd train input_torch_medium.json`. ### Curves: #### dpa2  ##### Performance We tested with torch==2.6.0.dev20241219+cu118 | Pytorch(eager) | Pytorch(compile) | Paddle(eager) | Paddle(CINN compile) | | -- | -- | -- | -- | | 0.1078s/step | compile do not support double-backward | 0.1130s/step | 0.0638s/step | #### se_atten  ##### Performance We tested with torch==2.6.0.dev20241219+cu118 | Pytorch(eager) | Pytorch(compile) | Paddle(eager) | Paddle(CINN compile) | | -- | -- | -- | -- | | 0.0342s/step | compile do not support double-backward | 0.0444s/step | 0.0244s/step | ### Accuracy details: #### dpa2 - Pytorch:  - Paddle(eager mode):  - Paddle(CINN compiler)  #### se_atten - Pytorch  - Paddle(eager_mode)  - Paddle(CINN compliler)  ### TODO: - [x] Fix high order backward of control flow in Paddle(PaddlePaddle/Paddle#70545) - [ ] Fix shape64 issue(PaddlePaddle/Paddle#70947) <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Enhanced training performance through optimization techniques that leverage compilation and profiling for better execution monitoring. - Introduced a new function for converting various input types to boolean values, improving environment variable handling. - **Refactor** - Improved precision management for training parameters and updated environment configuration handling to ensure robust optimization support. <!-- 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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…Paddle#70947) * add FLAGS_check_jit_instrction_shape * add log * add flag in runtime/flags * fix * tix typo * delete FLAGS_pir_apply_shape_optimization_pass * delete symbolic shape pass in trt * delete the test case of reshape and split op
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…Paddle#70947) * add FLAGS_check_jit_instrction_shape * add log * add flag in runtime/flags * fix * tix typo * delete FLAGS_pir_apply_shape_optimization_pass * delete symbolic shape pass in trt * delete the test case of reshape and split op
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PR Category
CINN
PR Types
Improvements
Description
Pcard-67164
After this PR merged, infer_symbolic and CINN will be strongly bound.