Move cpp code to directory csrcs (#42)

* move cpp code to csrcs

* move cpp code to csrcs

fastdeploy/core/fd_tensor.h

@@ -1,84 +0,0 @@
-// 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 <numeric>
-#include <string>
-#include <vector>
-
-#include "fastdeploy/core/fd_type.h"
-
-namespace fastdeploy {
-
-struct FASTDEPLOY_DECL FDTensor {
-  std::vector<int8_t> data;
-  std::vector<int64_t> shape;
-  std::string name = "";
-  FDDataType dtype;
-
-  // This use to skip memory copy step
-  // the external_data_ptr will point to the user allocated memory
-  // user has to maintain the memory, allocate and release
-  void* external_data_ptr = nullptr;
-  // The internal data will be on CPU
-  // Some times, the external data is on the GPU, and we are going to use
-  // GPU to inference the model
-  // so we can skip data transfer, which may improve the efficience
-  Device device = Device::CPU;
-
-  // if the external data is not on CPU, we use this temporary buffer
-  // to transfer data to CPU at some cases we need to visit the
-  // other devices' data
-  std::vector<int8_t> temporary_cpu_buffer;
-
-  // Get data buffer pointer
-  void* MutableData();
-
-  // Use this data to get the tensor data to process
-  // Since the most senario is process data in CPU
-  // this function weill return a pointer to cpu memory
-  // buffer.
-  // If the original data is on other device, the data
-  // will copy to cpu store in `temporary_cpu_buffer`
-  void* Data();
-
-  // Set user memory buffer for Tensor, the memory is managed by
-  // the user it self, but the Tensor will share the memory with user
-  // So take care with the user buffer
-  void SetExternalData(const std::vector<int>& new_shape,
-                       const FDDataType& data_type, void* data_buffer);
-
-  // Initialize Tensor
-  // Include setting attribute for tensor
-  // and allocate cpu memory buffer
-  void Allocate(const std::vector<int>& new_shape, const FDDataType& data_type,
-                const std::string& tensor_name = "");
-
-  // Total size of tensor memory buffer in bytes
-  int Nbytes() const;
-
-  // Total number of elements in this tensor
-  int Numel() const;
-
-  // Debug function
-  // Use this function to print shape, dtype, mean, max, min
-  // prefix will also be printed as tag
-  void PrintInfo(const std::string& prefix = "TensorInfo: ");
-
-  FDTensor() {}
-  explicit FDTensor(const std::string& tensor_name);
-};
-
-} // namespace fastdeploy