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Add ShapeOptimizationPass for SymbolicDim constraint construction. (#…
…57069) * add constraint_pass for symbolicDim construction. * add UT.
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109 changes: 109 additions & 0 deletions
109
paddle/pir/dialect/shape/transforms/shape_optimization_pass.cc
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| // Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
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| #include "paddle/pir/dialect/shape/transforms/shape_optimization_pass.h" | ||
| #include "paddle/fluid/pir/dialect/operator/ir/op_type.h" | ||
| #include "paddle/pir/dialect/shape/ir/shape_op.h" | ||
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| #include "paddle/pir/core/builtin_op.h" | ||
| #include "paddle/pir/core/program.h" | ||
| #include "paddle/pir/pass/pass.h" | ||
| #include "paddle/pir/pass/pass_registry.h" | ||
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| namespace { | ||
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| bool InsertTieShapeOnValue(pir::OpResult value, | ||
| pir::Builder& builder) { // NOLINT | ||
| auto ty = value.type().dyn_cast<paddle::dialect::DenseTensorType>(); | ||
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| if (!ty || ty.dims().size() == 0) return true; | ||
| std::vector<pir::OpResult> dimSizes; | ||
| for (int64_t dim = 0, rank = ty.dims().size(); dim < rank; ++dim) { | ||
| auto dimOp = builder.Build<pir::dialect::TensorDimOp>(value, dim); | ||
| dimSizes.push_back(dimOp.out()); | ||
| } | ||
| builder.Build<pir::dialect::TieShapeOp>(value, dimSizes); | ||
| return true; | ||
| } | ||
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| bool InsertTieShapeOnRegion(pir::Region* region); | ||
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| bool InsertTieShapeOnOperation(pir::Operation* op, | ||
| pir::Builder& builder) { // NOLINT | ||
| if (op->isa<pir::dialect::TieShapeOp>()) return true; | ||
| // TODO(liujinnan): skip the specialized Ops. | ||
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| for (size_t i = 0; i < op->num_regions(); ++i) { | ||
| if (!InsertTieShapeOnRegion(&(op->region(i)))) return false; | ||
| } | ||
| builder.SetInsertionPointAfter(op); | ||
| for (pir::OpResult v : op->results()) { | ||
| if (!InsertTieShapeOnValue(v, builder)) return false; | ||
| } | ||
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| return true; | ||
| } | ||
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| bool insertTieShapeOnBlock(pir::Block* block) { | ||
| pir::Builder builder = | ||
| pir::Builder(pir::IrContext::Instance(), block, block->begin()); | ||
| // TODO(liujinnan): mapping block arguments | ||
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| std::vector<pir::Operation*> op_list; | ||
| for (pir::Operation* op : *block) op_list.push_back(op); | ||
| for (pir::Operation* op : op_list) { | ||
| if (!InsertTieShapeOnOperation(op, builder)) return false; | ||
| } | ||
| return true; | ||
| } | ||
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| bool InsertTieShapeOnRegion(pir::Region* region) { | ||
| for (pir::Block* block : *region) { | ||
| if (!insertTieShapeOnBlock(block)) return false; | ||
| } | ||
| return true; | ||
| } | ||
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| bool MaterializeShapeComputation(pir::ModuleOp m) { | ||
| if (!InsertTieShapeOnRegion(&(m->region(0)))) return false; | ||
| // TODO(liujinnan): add rewitter pattern for reifyInferShape. | ||
| return true; | ||
| } | ||
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| class ShapeOptimizationPass : public pir::Pass { | ||
| public: | ||
| ShapeOptimizationPass() : pir::Pass("shape_optimization", 0) {} | ||
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| void Run(pir::Operation* op) override { | ||
| auto module_op = op->dyn_cast<pir::ModuleOp>(); | ||
| IR_ENFORCE(module_op, "ShapeOptimizationPass should run on module op."); | ||
| MaterializeShapeComputation(module_op); | ||
| } | ||
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| bool CanApplyOn(pir::Operation* op) const override { | ||
| return op->name() == "builtin.module" && op->num_regions() > 0; | ||
| } | ||
| }; | ||
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| } // namespace | ||
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| namespace pir { | ||
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| std::unique_ptr<Pass> CreateShapeOptimizationPass() { | ||
| return std::make_unique<ShapeOptimizationPass>(); | ||
| } | ||
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| } // namespace pir | ||
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| REGISTER_IR_PASS(shape_optimization, ShapeOptimizationPass); |
26 changes: 26 additions & 0 deletions
26
paddle/pir/dialect/shape/transforms/shape_optimization_pass.h
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| // Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // http://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
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| #pragma once | ||
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| #include <memory> | ||
| #include "paddle/pir/core/dll_decl.h" | ||
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| namespace pir { | ||
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| class Pass; | ||
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| IR_API std::unique_ptr<Pass> CreateShapeOptimizationPass(); | ||
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| } // namespace pir |
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