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			89 lines
		
	
	
		
			2.8 KiB
		
	
	
	
		
			C++
		
	
	
		
			Executable File
		
	
	
	
	
			
		
		
	
	
			89 lines
		
	
	
		
			2.8 KiB
		
	
	
	
		
			C++
		
	
	
		
			Executable File
		
	
	
	
	
| // Copyright (c) 2022 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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| 
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| #pragma once
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| 
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| #include <iostream>
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| #include <memory>
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| #include <string>
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| #include <vector>
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| 
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| #include "fastdeploy/backends/backend.h"
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| #include "paddle_api.h"  // NOLINT
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| 
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| namespace fastdeploy {
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| 
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| struct LiteBackendOption {
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|   // cpu num threads
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|   int threads = 1;
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|   // lite power mode
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|   // 0: LITE_POWER_HIGH
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|   // 1: LITE_POWER_LOW
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|   // 2: LITE_POWER_FULL
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|   // 3: LITE_POWER_NO_BIND
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|   // 4: LITE_POWER_RAND_HIGH
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|   // 5: LITE_POWER_RAND_LOW
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|   int power_mode = 3;
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|   // enable fp16
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|   bool enable_fp16 = false;
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|   // enable int8
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|   bool enable_int8 = false;
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|   // optimized model dir for CxxConfig
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|   std::string optimized_model_dir = "";
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|   // TODO(qiuyanjun): support more options for lite backend.
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|   // Such as fp16, different device target (kARM/kXPU/kNPU/...)
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|   std::string nnadapter_subgraph_partition_config_path = "";
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|   bool enable_timvx = false;
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| };
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| 
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| // Convert data type from paddle lite to fastdeploy
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| FDDataType LiteDataTypeToFD(const paddle::lite_api::PrecisionType& dtype);
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| 
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| class LiteBackend : public BaseBackend {
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|  public:
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|   LiteBackend() {}
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|   virtual ~LiteBackend() = default;
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|   void BuildOption(const LiteBackendOption& option);
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| 
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|   bool InitFromPaddle(const std::string& model_file,
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|                       const std::string& params_file,
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|                       const LiteBackendOption& option = LiteBackendOption());
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| 
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|   bool Infer(std::vector<FDTensor>& inputs,
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|             std::vector<FDTensor>* outputs,
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|             bool copy_to_fd = true) override; // NOLINT
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| 
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|   int NumInputs() const override { return inputs_desc_.size(); }
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| 
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|   int NumOutputs() const override { return outputs_desc_.size(); }
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| 
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|   TensorInfo GetInputInfo(int index) override;
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|   TensorInfo GetOutputInfo(int index) override;
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|   std::vector<TensorInfo> GetInputInfos() override;
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|   std::vector<TensorInfo> GetOutputInfos() override;
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| 
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|  private:
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|   paddle::lite_api::CxxConfig config_;
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|   std::shared_ptr<paddle::lite_api::PaddlePredictor> predictor_;
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|   std::vector<TensorInfo> inputs_desc_;
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|   std::vector<TensorInfo> outputs_desc_;
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|   std::map<std::string, int> inputs_order_;
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|   LiteBackendOption option_;
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|   bool supported_fp16_ = false;
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|   bool ReadFile(const std::string& filename,
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|                std::vector<char>* contents,
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|                const bool binary = true);
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| };
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| }  // namespace fastdeploy
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