718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
55 lines
1.6 KiB
C++
55 lines
1.6 KiB
C++
// Tencent is pleased to support the open source community by making ncnn available.
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//
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// Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
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//
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// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
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// in compliance with the License. You may obtain a copy of the License at
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//
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// https://opensource.org/licenses/BSD-3-Clause
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//
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// Unless required by applicable law or agreed to in writing, software distributed
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// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
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// CONDITIONS OF ANY KIND, either express or implied. See the License for the
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// specific language governing permissions and limitations under the License.
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#include <mlir/IR/MLIRContext.h>
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#include <mlir/IR/PatternMatch.h>
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#include <mlir/Pass/Pass.h>
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#include <mlir/Transforms/GreedyPatternRewriteDriver.h>
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#include "tf_dialect.h"
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#include "ncnn_dialect.h"
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using namespace mlir;
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namespace mlir {
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namespace ncnn {
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#include "ncnn_rewriter.inc"
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class NCNNOptimizePass : public PassWrapper<NCNNOptimizePass, FunctionPass>
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{
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public:
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void runOnFunction();
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};
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void NCNNOptimizePass::runOnFunction()
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{
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mlir::OwningRewritePatternList patterns;
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mlir::ncnn::populateWithGenerated(&getContext(), patterns);
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(void)mlir::applyPatternsAndFoldGreedily(getFunction(), std::move(patterns));
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}
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std::unique_ptr<OperationPass<FuncOp> > createNCNNOptimizePass()
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{
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return std::make_unique<NCNNOptimizePass>();
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}
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static PassRegistration<NCNNOptimizePass> pass("ncnn-optimize", "ncnn optimization");
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} // namespace ncnn
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} // namespace mlir
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