[Other] [Part2] Upgrade runtime module (#1080)

[Other] Upgrade runtime module

fastdeploy/runtime/backends/paddle/paddle_backend.h

@@ -0,0 +1,91 @@
+// Copyright (c) 2022 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.
+
+#pragma once
+
+#include <iostream>
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "fastdeploy/runtime/backends/backend.h"
+#include "fastdeploy/runtime/backends/paddle/option.h"
+#ifdef ENABLE_PADDLE_FRONTEND
+#include "paddle2onnx/converter.h"
+#endif
+#include "fastdeploy/utils/unique_ptr.h"
+#include "paddle_inference_api.h"  // NOLINT
+
+namespace fastdeploy {
+
+// convert FD device to paddle place type
+paddle_infer::PlaceType ConvertFDDeviceToPlace(Device device);
+
+// Share memory buffer with paddle_infer::Tensor from fastdeploy::FDTensor
+void ShareTensorFromFDTensor(paddle_infer::Tensor* tensor, FDTensor& fd_tensor);
+
+// convert paddle_infer::Tensor to fastdeploy::FDTensor
+// if copy_to_fd is true, copy memory data to FDTensor
+/// else share memory to FDTensor
+void PaddleTensorToFDTensor(std::unique_ptr<paddle_infer::Tensor>& tensor,
+                            FDTensor* fd_tensor, bool copy_to_fd);
+
+// Convert data type from paddle inference to fastdeploy
+FDDataType PaddleDataTypeToFD(const paddle_infer::DataType& dtype);
+
+// Convert data type from paddle2onnx::PaddleReader to fastdeploy
+FDDataType ReaderDataTypeToFD(int32_t dtype);
+
+class PaddleBackend : public BaseBackend {
+ public:
+  PaddleBackend() {}
+  virtual ~PaddleBackend() = default;
+  void BuildOption(const PaddleBackendOption& option);
+
+  bool
+  InitFromPaddle(const std::string& model_file, const std::string& params_file,
+                 const PaddleBackendOption& option = PaddleBackendOption());
+
+  bool Infer(std::vector<FDTensor>& inputs, std::vector<FDTensor>* outputs,
+             bool copy_to_fd = true) override;
+
+  int NumInputs() const override { return inputs_desc_.size(); }
+
+  int NumOutputs() const override { return outputs_desc_.size(); }
+
+  std::unique_ptr<BaseBackend> Clone(void* stream = nullptr,
+                                     int device_id = -1) override;
+
+  TensorInfo GetInputInfo(int index) override;
+  TensorInfo GetOutputInfo(int index) override;
+  std::vector<TensorInfo> GetInputInfos() override;
+  std::vector<TensorInfo> GetOutputInfos() override;
+
+ private:
+  void
+  CollectShapeRun(paddle_infer::Predictor* predictor,
+                  const std::map<std::string, std::vector<int>>& shape) const;
+  void GetDynamicShapeFromOption(
+      const PaddleBackendOption& option,
+      std::map<std::string, std::vector<int>>* max_shape,
+      std::map<std::string, std::vector<int>>* min_shape,
+      std::map<std::string, std::vector<int>>* opt_shape) const;
+  void SetTRTDynamicShapeToConfig(const PaddleBackendOption& option);
+  PaddleBackendOption option_;
+  paddle_infer::Config config_;
+  std::shared_ptr<paddle_infer::Predictor> predictor_;
+  std::vector<TensorInfo> inputs_desc_;
+  std::vector<TensorInfo> outputs_desc_;
+};
+}  // namespace fastdeploy