[CINN]add CacheGradOpSymbolicShapeInterface #65343
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…ckward-cache-interface
zyfncg
reviewed
Jun 24, 2024
| @@ -113,7 +125,7 @@ void ApplyCinnPreprocessPass( | |||
| bool has_dynamic_shape = HasDynamicShape(*program); | |||
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| if (has_dynamic_shape) { | |||
| pass_manager->AddPass(pir::CreateShapeOptimizationPass()); | |||
| // pass_manager->AddPass(pir::CreateShapeOptimizationPass()); | |||
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| namespace paddle::dialect { | ||
| using CacheGradOpSymbolicShapeInterface = | ||
| pir::CacheGradOpSymbolicShapeInterface; |
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这个inferface是否有必要包一层paddle::dialect?
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CacheGradOpSymbolicShapeInterface属于op接口最好放在paddle::dialect，但是和符号推导接口类似，由于pir目录下的shape_optimization_pass需要使用，而pir不能引用paddle::dialect，所以放在pir中了。
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| const auto& CacheSelfSymbolicShape = [&]() { | ||
| std::vector<symbol::ShapeOrDataDimExprs> result_shape_or_data; | ||
| for (auto& result : op->results()) { | ||
| result_shape_or_data.emplace_back( | ||
| infer_context->GetShapeOrDataForValue(result)); | ||
| } | ||
| if (infer_context->GetOpInferSymbolicShapeCache(op_infer_cache_key) | ||
| .has_value()) { | ||
| std::vector<symbol::ShapeOrDataDimExprs> cached_result_shape_or_data = | ||
| infer_context->GetOpInferSymbolicShapeCache(op_infer_cache_key) | ||
| .value(); | ||
| // check whether the result_shape_or_data is consistent with the cached | ||
| // TODO(Hongqing-work): delete check and only set cache for op without | ||
| // InferSymbolicShapeInterface after fixing all warnings. | ||
| if (cached_result_shape_or_data.size() != result_shape_or_data.size()) { | ||
| LOG(WARNING) << "cached shape is not consistent with real shape"; | ||
| } else { | ||
| for (uint32_t i = 0; i < op->num_results(); ++i) { | ||
| if (cached_result_shape_or_data[i] != result_shape_or_data[i]) { | ||
| LOG(WARNING) << "cached shape is not consistent with real shape"; | ||
| VLOG(3) << "InferSymbolicShapeCacheKey is: " << op_infer_cache_key; | ||
| VLOG(3) << "cached shape is: " << cached_result_shape_or_data[i]; | ||
| VLOG(3) << "real shape is: " << result_shape_or_data[i]; | ||
| } | ||
| } | ||
| } | ||
| } else { | ||
| infer_context->SetOpInferSymbolicShapeCache(op_infer_cache_key, | ||
| result_shape_or_data); | ||
| } | ||
| }; | ||
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| const auto& CacheGradOpSymbolicShape = [&]() { | ||
| auto cache_grad_op_symbolic_shape_interface = | ||
| op->dyn_cast<pir::CacheGradOpSymbolicShapeInterface>(); | ||
| if (cache_grad_op_symbolic_shape_interface) { | ||
| VLOG(3) << "CacheGradOpSymbolicShape for: " << op->name(); | ||
| PADDLE_ENFORCE_EQ( | ||
| cache_grad_op_symbolic_shape_interface.CacheGradOpSymbolicShape( | ||
| infer_context), | ||
| true, | ||
| "CacheGradOpSymbolicShape for %s failed.", | ||
| op->name()); | ||
| } | ||
| }; |
tc20042008
reviewed
Jun 26, 2024
| void InferSymExprForOp(Operation* op, | ||
| InferSymbolicShapeContext* infer_context, | ||
| const InferSymbolicShapeCacheKey& op_infer_cache_key) { | ||
| auto infer_symbolic_shape_interface = |
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const auto&
不要养成使用auto的习惯。最多能用auto*和const auto&
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这里需要调用非const函数，和其它接口保持一致，所以做此折中
| } | ||
| } | ||
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| void CacheSelfSymbolicShape( |
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已修改为forward和backward
| LOG(WARNING) << "cached shape is not consistent with real shape"; | ||
| } else { | ||
| for (uint32_t i = 0; i < op->num_results(); ++i) { | ||
| if (cached_result_shape_or_data[i] != result_shape_or_data[i]) { |
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到这里已经是三层if了。
既然从第二层if到这里的逻辑都只是check，那就专门提一个check函数。
tc20042008
approved these changes
Jun 27, 2024
zyfncg
approved these changes
Jun 27, 2024
zhangbo9674
approved these changes
Jun 27, 2024
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PR Category
CINN
PR Types
New features
Description
Pcard-67164
This PR adds CacheGradOpSymbolicShapeInterface.