60 lines
2.0 KiB
C++
60 lines
2.0 KiB
C++
// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "paddle/cinn/pass/pass.h"
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namespace cinn {
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namespace optim {
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class RemoveScheduleBlockPass : public BlockPass {
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public:
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RemoveScheduleBlockPass() : BlockPass("remove_schedule_block") {}
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LogicalResult Run(ir::stmt::BlockRef block) override;
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};
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/**
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* Removes ScheduleBlock nodes from the IR tree.
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*
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* This pass is applicable in scenarios where ScheduleBlock nodes are present in
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* the IR tree but are no longer needed for further optimization.
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*
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* When applied, this pass will traverse the IR tree and replace each
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* ScheduleBlockRealize node with its body. During this process, it will also
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* replace the iter_vars in the body with their corresponding iter_values. This
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* effectively removes the ScheduleBlock structure while preserving the
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* computational logic within it.
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*
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* Performance impact: This pass addresses the overhead of maintaining
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* ScheduleBlock structures in the IR. By removing these structures, it
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* simplifies the IR, which can lead to faster subsequent passes and potentially
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* more efficient code generation.
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*
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* Examples:
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* 1. Basic ScheduleBlock removal:
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* Input IR:
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* ScheduleBlock {
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* iter_vars: [i, j]
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* iter_values: [0, 1]
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* body {
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* body: A[i, j] = B[i, j] + C[i, j]
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* }
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* }
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* Output IR:
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* A[0, 1] = B[0, 1] + C[0, 1]
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*/
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std::unique_ptr<BlockPass> CreateRemoveScheduleBlockPass();
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} // namespace optim
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} // namespace cinn
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