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
53 lines
1.6 KiB
C++
53 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) 2021 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 "pass_level1.h"
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#include "../utils.h"
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namespace pnnx {
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class UpsamplingBilinear2d : public FuseModulePass
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{
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public:
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const char* match_type_str() const
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{
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return "__torch__.torch.nn.modules.upsampling.UpsamplingBilinear2d";
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}
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const char* type_str() const
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{
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return "nn.UpsamplingBilinear2d";
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}
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void write(Operator* op, const std::shared_ptr<torch::jit::Graph>& graph) const
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{
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const torch::jit::Node* upsample = find_node_by_kind(graph, "aten::upsample_bilinear2d");
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if (upsample->hasNamedInput("output_size"))
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{
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op->params["size"] = upsample->namedInput("output_size");
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}
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if (upsample->hasNamedInput("scale_factors"))
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{
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op->params["scale_factor"] = upsample->namedInput("scale_factors");
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}
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}
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};
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REGISTER_GLOBAL_PNNX_FUSE_MODULE_PASS(UpsamplingBilinear2d)
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} // namespace pnnx
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